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Senior Data Scientist

AT&T

Software and Technology Jobs

Senior Data Scientist

full-timePosted: Dec 1, 2025

Job Description

Job Description:

At AT&T we’re redefining the future of communication by connecting people to greater possibility with expertise, simplicity, and inspiration. At the heart of our purpose lies a diverse workforce of 200,000 people and a culture that aspires to serve customers first, act boldly, move faster, and win as one.

Our Product Development group, part of AT&T’s Technology Services (ATS) organization, is responsible for building software-based products, services, and platforms that our customers love and need. Harnessing technology and rebuilding software expertise, the team is inspiring simplicity with projects that deliver revenue and cost savings opportunities.

Job Overview

AT&T is building a new era of intelligent automation. We are looking for a highly skilled Senior Data Scientist with advanced Python expertise to design, develop, and integrate intelligent systems focused on large language models (LLMs), prompt engineering, and advanced context management. You will architect context-rich AI solutions, craft effective prompts, and ensure seamless agent interactions using frameworks like LangGraph and AutoGen, with robust observability and experimentation powered by Langfuse.

As a Senior Data Scientist, you will architect, build, and deploy context-driven AI solutions that transform how entire organizations work and deliver value. You’ll leverage LLMs, Retrieval-Augmented Generation (RAG), and next‑gen AI agents to automate complex workflows, driving productivity, efficiency, and measurable outcomes. You will also produce clear technical R&D reports that document experiments, metrics, trade-offs, and recommendations for stakeholders.

Core Responsibilities

  • Design, optimize, and evaluate prompts for LLMs to achieve precise, contextually appropriate outputs across diverse use cases.

  • Architect and implement dynamic context management strategies, including session memory, retrieval-augmented generation, and user personalization to enhance agent performance.

  • Build and manage agentic workflows and multi-agent systems using frameworks such as LangGraph and AutoGen.

  • Integrate, fine-tune, and orchestrate LLMs within Python-based applications, leveraging APIs and custom pipelines for scalable deployment.

  • Implement observability, tracing, evaluation, and experiment management using Langfuse; define and track key metrics (quality, latency, cost).

  • Develop and maintain robust backend services, APIs, and (optionally) front-end interfaces to deliver end‑to‑end AI applications.

  • Produce concise, technically rigorous R&D reports that document problem framing, methodology, experiment design, results, and recommended next steps.

  • Work closely with product, data science, and engineering teams to define requirements, run prompt/agent experiments, and iterate quickly on solutions.

  • Apply and advocate best practices in software engineering, code quality, testing, DevOps, and secure, ethical AI automation.

Skills, Knowledge, and Experience

Day-to-Day

  • Design and develop agentic AI solutions and intelligent automation workflows using LLMs, prompt engineering, context management, and multi-agent orchestration (AutoGen, LangGraph).

  • Collaborate with cross-functional teams to define and refine requirements, run experiments, and iterate on AI-driven solutions.

  • Architect and integrate scalable, production-grade Python applications for AI agent deployment.

  • Use Langfuse to trace, evaluate, and compare prompt and agent versions; maintain experiment logs and dashboards.

  • Participate in code reviews, contribute to best practices, and mentor peers on AI automation technologies and frameworks.

  • Produce clear technical R&D reports summarizing approach, experiments, findings, and recommendations.

Technical Skills

  • Advanced skills in Python, including FastAPI, async I/O, typing/mypy, packaging, testing (pytest), performance profiling, and dependency management.

  • Advanced skills in AutoGen (multi-agent orchestration) and Langfuse (observability, tracing, evaluation, experiment management).

  • Demonstrated expertise in prompt engineering for LLMs (OpenAI, Anthropic, open-source LLMs).

  • Strong understanding of context engineering, including session management, vector search, and knowledge retrieval strategies; familiarity with RAG pipelines.

  • Hands-on experience integrating AI agents and LLMs into production systems.

  • Proficiency with agentic/conversational flow frameworks such as LangGraph and related orchestration tooling.

  • Experience with cloud infrastructure, containerization (Docker), and CI/CD practices.

  • Strong ability to write technical R&D reports: experiment design, methodology, metrics (quality, latency, cost), A/B testing, and executive-ready summaries.

  • Exceptional analytical, problem-solving, and communication skills.

Additional Desirable Experience

  • Experience evaluating and fine‑tuning LLMs or working with RAG architectures at scale.

  • Background in information retrieval, search, or knowledge management systems.

  • Contributions to open-source LLM, agent, or prompt engineering projects.

  • Experience with secure, ethical, and scalable deployment of AI solutions in enterprise environments.

Education

  • Minimum: Master’s degree in Computer Science, Data Science, Electrical Engineering, Mathematics, Statistics, or a closely related field.

  • Preferred: PhD (or current PhD candidate/ABD) with demonstrated research and experimentation experience in relevant areas (LLMs, IR, ML systems, NLP, agentic AI).

Benefits

A career with us, a global leader in communications and technology, comes with big rewards. We offer a competitive salary plus an annual company performance bonus. Once you are a part of the team, you will gain some amazing perks and benefits including car allowance, wellness & leisure time contribution, sickness compensation plan, premium medical services, family friendly benefits as well as meal contribution and an extra week of vacation (…and much more).

Salary

CZE: Base salary from 91 400 CZK gross a month. The actual salary is based on skills, experience and knowledge.

SVK: Base salary from 3130 EUR gross a month. The actual salary is based on skills, experience and knowledge.

Weekly Hours:

40

Time Type:

Regular

Location:

Brno, Czechia

It is the policy of AT&T to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, AT&T will provide reasonable accommodations for qualified individuals with disabilities. AT&T is a fair chance employer and does not initiate a background check until an offer is made.

Locations

  • Brno, Jihomoravský kraj, Czechia

Salary

Estimated Salary Rangemedium confidence

45,000 - 85,000 USD / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • Advanced skills in Python, including FastAPI, async I/O, typing/mypy, packaging, testing (pytest), performance profiling, and dependency managementintermediate
  • Advanced skills in AutoGen (multi-agent orchestration) and Langfuse (observability, tracing, evaluation, experiment management)intermediate
  • Demonstrated expertise in prompt engineering for LLMs (OpenAI, Anthropic, open-source LLMs)intermediate
  • Strong understanding of context engineering, including session management, vector search, and knowledge retrieval strategies; familiarity with RAG pipelinesintermediate
  • Hands-on experience integrating AI agents and LLMs into production systemsintermediate
  • Proficiency with agentic/conversational flow frameworks such as LangGraph and related orchestration toolingintermediate
  • Experience with cloud infrastructure, containerization (Docker), and CI/CD practicesintermediate
  • Strong ability to write technical R&D reports: experiment design, methodology, metrics (quality, latency, cost), A/B testing, and executive-ready summariesintermediate
  • Exceptional analytical, problem-solving, and communication skillsintermediate

Required Qualifications

  • Master’s degree in Computer Science, Data Science, Electrical Engineering, Mathematics, Statistics, or a closely related field (experience)

Preferred Qualifications

  • PhD (or current PhD candidate/ABD) with demonstrated research and experimentation experience in relevant areas (LLMs, IR, ML systems, NLP, agentic AI) (experience)
  • Experience evaluating and fine-tuning LLMs or working with RAG architectures at scale (experience)
  • Background in information retrieval, search, or knowledge management systems (experience)
  • Contributions to open-source LLM, agent, or prompt engineering projects (experience)
  • Experience with secure, ethical, and scalable deployment of AI solutions in enterprise environments (experience)

Responsibilities

  • Design, optimize, and evaluate prompts for LLMs to achieve precise, contextually appropriate outputs across diverse use cases
  • Architect and implement dynamic context management strategies, including session memory, retrieval-augmented generation, and user personalization to enhance agent performance
  • Build and manage agentic workflows and multi-agent systems using frameworks such as LangGraph and AutoGen
  • Integrate, fine-tune, and orchestrate LLMs within Python-based applications, leveraging APIs and custom pipelines for scalable deployment
  • Implement observability, tracing, evaluation, and experiment management using Langfuse; define and track key metrics (quality, latency, cost)
  • Develop and maintain robust backend services, APIs, and (optionally) front-end interfaces to deliver end-to-end AI applications
  • Produce concise, technically rigorous R&D reports that document problem framing, methodology, experiment design, results, and recommended next steps
  • Work closely with product, data science, and engineering teams to define requirements, run prompt/agent experiments, and iterate quickly on solutions
  • Apply and advocate best practices in software engineering, code quality, testing, DevOps, and secure, ethical AI automation

Benefits

  • general: Competitive salary plus an annual company performance bonus
  • general: Car allowance
  • general: Wellness & leisure time contribution
  • general: Sickness compensation plan
  • general: Premium medical services
  • general: Family friendly benefits
  • general: Meal contribution
  • general: An extra week of vacation

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AT&T logo

Senior Data Scientist

AT&T

Software and Technology Jobs

Senior Data Scientist

full-timePosted: Dec 1, 2025

Job Description

Job Description:

At AT&T we’re redefining the future of communication by connecting people to greater possibility with expertise, simplicity, and inspiration. At the heart of our purpose lies a diverse workforce of 200,000 people and a culture that aspires to serve customers first, act boldly, move faster, and win as one.

Our Product Development group, part of AT&T’s Technology Services (ATS) organization, is responsible for building software-based products, services, and platforms that our customers love and need. Harnessing technology and rebuilding software expertise, the team is inspiring simplicity with projects that deliver revenue and cost savings opportunities.

Job Overview

AT&T is building a new era of intelligent automation. We are looking for a highly skilled Senior Data Scientist with advanced Python expertise to design, develop, and integrate intelligent systems focused on large language models (LLMs), prompt engineering, and advanced context management. You will architect context-rich AI solutions, craft effective prompts, and ensure seamless agent interactions using frameworks like LangGraph and AutoGen, with robust observability and experimentation powered by Langfuse.

As a Senior Data Scientist, you will architect, build, and deploy context-driven AI solutions that transform how entire organizations work and deliver value. You’ll leverage LLMs, Retrieval-Augmented Generation (RAG), and next‑gen AI agents to automate complex workflows, driving productivity, efficiency, and measurable outcomes. You will also produce clear technical R&D reports that document experiments, metrics, trade-offs, and recommendations for stakeholders.

Core Responsibilities

  • Design, optimize, and evaluate prompts for LLMs to achieve precise, contextually appropriate outputs across diverse use cases.

  • Architect and implement dynamic context management strategies, including session memory, retrieval-augmented generation, and user personalization to enhance agent performance.

  • Build and manage agentic workflows and multi-agent systems using frameworks such as LangGraph and AutoGen.

  • Integrate, fine-tune, and orchestrate LLMs within Python-based applications, leveraging APIs and custom pipelines for scalable deployment.

  • Implement observability, tracing, evaluation, and experiment management using Langfuse; define and track key metrics (quality, latency, cost).

  • Develop and maintain robust backend services, APIs, and (optionally) front-end interfaces to deliver end‑to‑end AI applications.

  • Produce concise, technically rigorous R&D reports that document problem framing, methodology, experiment design, results, and recommended next steps.

  • Work closely with product, data science, and engineering teams to define requirements, run prompt/agent experiments, and iterate quickly on solutions.

  • Apply and advocate best practices in software engineering, code quality, testing, DevOps, and secure, ethical AI automation.

Skills, Knowledge, and Experience

Day-to-Day

  • Design and develop agentic AI solutions and intelligent automation workflows using LLMs, prompt engineering, context management, and multi-agent orchestration (AutoGen, LangGraph).

  • Collaborate with cross-functional teams to define and refine requirements, run experiments, and iterate on AI-driven solutions.

  • Architect and integrate scalable, production-grade Python applications for AI agent deployment.

  • Use Langfuse to trace, evaluate, and compare prompt and agent versions; maintain experiment logs and dashboards.

  • Participate in code reviews, contribute to best practices, and mentor peers on AI automation technologies and frameworks.

  • Produce clear technical R&D reports summarizing approach, experiments, findings, and recommendations.

Technical Skills

  • Advanced skills in Python, including FastAPI, async I/O, typing/mypy, packaging, testing (pytest), performance profiling, and dependency management.

  • Advanced skills in AutoGen (multi-agent orchestration) and Langfuse (observability, tracing, evaluation, experiment management).

  • Demonstrated expertise in prompt engineering for LLMs (OpenAI, Anthropic, open-source LLMs).

  • Strong understanding of context engineering, including session management, vector search, and knowledge retrieval strategies; familiarity with RAG pipelines.

  • Hands-on experience integrating AI agents and LLMs into production systems.

  • Proficiency with agentic/conversational flow frameworks such as LangGraph and related orchestration tooling.

  • Experience with cloud infrastructure, containerization (Docker), and CI/CD practices.

  • Strong ability to write technical R&D reports: experiment design, methodology, metrics (quality, latency, cost), A/B testing, and executive-ready summaries.

  • Exceptional analytical, problem-solving, and communication skills.

Additional Desirable Experience

  • Experience evaluating and fine‑tuning LLMs or working with RAG architectures at scale.

  • Background in information retrieval, search, or knowledge management systems.

  • Contributions to open-source LLM, agent, or prompt engineering projects.

  • Experience with secure, ethical, and scalable deployment of AI solutions in enterprise environments.

Education

  • Minimum: Master’s degree in Computer Science, Data Science, Electrical Engineering, Mathematics, Statistics, or a closely related field.

  • Preferred: PhD (or current PhD candidate/ABD) with demonstrated research and experimentation experience in relevant areas (LLMs, IR, ML systems, NLP, agentic AI).

Benefits

A career with us, a global leader in communications and technology, comes with big rewards. We offer a competitive salary plus an annual company performance bonus. Once you are a part of the team, you will gain some amazing perks and benefits including car allowance, wellness & leisure time contribution, sickness compensation plan, premium medical services, family friendly benefits as well as meal contribution and an extra week of vacation (…and much more).

Salary

CZE: Base salary from 91 400 CZK gross a month. The actual salary is based on skills, experience and knowledge.

SVK: Base salary from 3130 EUR gross a month. The actual salary is based on skills, experience and knowledge.

Weekly Hours:

40

Time Type:

Regular

Location:

Brno, Czechia

It is the policy of AT&T to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, AT&T will provide reasonable accommodations for qualified individuals with disabilities. AT&T is a fair chance employer and does not initiate a background check until an offer is made.

Locations

  • Brno, Jihomoravský kraj, Czechia

Salary

Estimated Salary Rangemedium confidence

45,000 - 85,000 USD / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • Advanced skills in Python, including FastAPI, async I/O, typing/mypy, packaging, testing (pytest), performance profiling, and dependency managementintermediate
  • Advanced skills in AutoGen (multi-agent orchestration) and Langfuse (observability, tracing, evaluation, experiment management)intermediate
  • Demonstrated expertise in prompt engineering for LLMs (OpenAI, Anthropic, open-source LLMs)intermediate
  • Strong understanding of context engineering, including session management, vector search, and knowledge retrieval strategies; familiarity with RAG pipelinesintermediate
  • Hands-on experience integrating AI agents and LLMs into production systemsintermediate
  • Proficiency with agentic/conversational flow frameworks such as LangGraph and related orchestration toolingintermediate
  • Experience with cloud infrastructure, containerization (Docker), and CI/CD practicesintermediate
  • Strong ability to write technical R&D reports: experiment design, methodology, metrics (quality, latency, cost), A/B testing, and executive-ready summariesintermediate
  • Exceptional analytical, problem-solving, and communication skillsintermediate

Required Qualifications

  • Master’s degree in Computer Science, Data Science, Electrical Engineering, Mathematics, Statistics, or a closely related field (experience)

Preferred Qualifications

  • PhD (or current PhD candidate/ABD) with demonstrated research and experimentation experience in relevant areas (LLMs, IR, ML systems, NLP, agentic AI) (experience)
  • Experience evaluating and fine-tuning LLMs or working with RAG architectures at scale (experience)
  • Background in information retrieval, search, or knowledge management systems (experience)
  • Contributions to open-source LLM, agent, or prompt engineering projects (experience)
  • Experience with secure, ethical, and scalable deployment of AI solutions in enterprise environments (experience)

Responsibilities

  • Design, optimize, and evaluate prompts for LLMs to achieve precise, contextually appropriate outputs across diverse use cases
  • Architect and implement dynamic context management strategies, including session memory, retrieval-augmented generation, and user personalization to enhance agent performance
  • Build and manage agentic workflows and multi-agent systems using frameworks such as LangGraph and AutoGen
  • Integrate, fine-tune, and orchestrate LLMs within Python-based applications, leveraging APIs and custom pipelines for scalable deployment
  • Implement observability, tracing, evaluation, and experiment management using Langfuse; define and track key metrics (quality, latency, cost)
  • Develop and maintain robust backend services, APIs, and (optionally) front-end interfaces to deliver end-to-end AI applications
  • Produce concise, technically rigorous R&D reports that document problem framing, methodology, experiment design, results, and recommended next steps
  • Work closely with product, data science, and engineering teams to define requirements, run prompt/agent experiments, and iterate quickly on solutions
  • Apply and advocate best practices in software engineering, code quality, testing, DevOps, and secure, ethical AI automation

Benefits

  • general: Competitive salary plus an annual company performance bonus
  • general: Car allowance
  • general: Wellness & leisure time contribution
  • general: Sickness compensation plan
  • general: Premium medical services
  • general: Family friendly benefits
  • general: Meal contribution
  • general: An extra week of vacation

Target Your Resume for "Senior Data Scientist" , AT&T

Get personalized recommendations to optimize your resume specifically for Senior Data Scientist. Takes only 15 seconds!

AI-powered keyword optimization
Skills matching & gap analysis
Experience alignment suggestions

Check Your ATS Score for "Senior Data Scientist" , AT&T

Find out how well your resume matches this job's requirements. Get comprehensive analysis including ATS compatibility, keyword matching, skill gaps, and personalized recommendations.

ATS compatibility check
Keyword optimization analysis
Skill matching & gap identification
Format & readability score

Tags & Categories

TelecommunicationsTelecommunications

Answer 10 quick questions to check your fit for Senior Data Scientist @ AT&T.

Quiz Challenge
10 Questions
~2 Minutes
Instant Score

Related Books and Jobs

No related jobs found at the moment.