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Gen AI Engineer

Tata Consultancy Services
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Job Title: Gen AI Engineer
Location: McLean, Virginia

Job Summary
We are looking for talented and enthusiastic fresh graduates who have hands‑on experience with Python and have completed projects using modern programming technologies during their academic journey. Candidates should have foundational knowledge of AI concepts, familiarity with AI‑enabled tools, and strong communication skills to collaborate effectively with teams and stakeholders.

Key Responsibilities

  • Demonstrate strong understanding of Python programming through academic or project work.
  • Show passion for AI, eagerness to learn, and willingness to grow within the team.
  • Collaborate with team members to contribute to the development of AI‑driven solutions.
  • Leverage AI tools such as Copilot and prompt‑based AI solutions to improve productivity and solution quality.
  • Participate in AI application development by building and maintaining scalable backend services using Python and related frameworks.
  • Design and optimize RAG (Retrieval Augmented Generation) pipelines and workflows.
  • Integrate LLMs using frameworks such as LangChain to develop multi‑turn AI agents and intelligent orchestration flows.

Required Skills & Qualifications

  • Bachelor’s Degree in Computer Science, Data Science, or a related technical field.
  • Understanding of LLM capabilities, tokenization, and basic machine learning concepts.
  • Strong communication and presentation skills.
  • Ability to learn quickly and adapt to new and emerging technologies.
  • Strong analytical and problem‑solving abilities.
  • Team player with a positive attitude and strong work ethic.

Unique Experience from this Role

  • Exposure to real‑life development and testing bottlenecks, with opportunities to apply technology to solve practical challenges.
  • Hands‑on implementation of Gen AI concepts to optimize and enhance business processes.
  • Experience helping customers build AI agents that improve productivity and reduce operational costs.

Learning Outcomes

  • Opportunity to apply academic learning to real-world engineering challenges.
  • Gain exposure to new tools, technologies, and techniques, and understand their impact on SDLC cycles.
  • Develop strong analytical, problem‑solving, and critical‑thinking skills through hands‑on project experience.