Senior Engineer - Agentic AI

Overview

The Agentic AI Engineer is a hands‑on development role at TCS (Americas) specializing in building and deploying AI agent solutions for clients. In this client‑facing consulting position you will work in a hybrid environment, delivering cutting‑edge AI agents that blend large language models, custom prompts, data sources, and business logic across diverse industries such as finance, manufacturing, and travel.

• Develop AI Agents & Applications:
  Code the core logic for AI agents, whether standalone or in multi‑agent systems, enabling them to answer questions, generate content, or execute transactions.
• Coding with LLMs and Tools:
  Use Python or similar languages to integrate large language models (LLMs) and external tools such as APIs, web search, and databases.
• Prompt Engineering & Optimization:
  Craft, refine, and test prompts to guide agent behavior, including fallback strategies for uncertainty.
• Implement Retrieval‑Augmented Generation for Knowledge:
  Connect AI agents to vector databases or search indices to ground outputs in up‑to‑date, domain‑specific information.
• System Integration & APIs:
  Integrate AI agents with external systems such as travel booking APIs or payment gateways, handling formatting, RESTful calls, and data responses.
• Testing and Iteration:
  Simulate agent behavior, identify and fix failure modes, and tune prompts and code for high‑quality results.
• Deploy AI Solutions:
  Package and deploy agent applications using Docker or cloud platforms, ensuring scalability and proper configuration.
• Collaboration & Agile Delivery:
  Work with AI Architects, Data Engineers, and UX Developers in agile teams, contributing to sprints and client demos.
• Industry‑Specific Customization:
  Tailor solutions for each industry, adapting compliance, personalization, and integration as needed.
• Adhere to AI Ethics & Safety:
  Implement guardrails, content moderation, and privacy measures following TCS’s responsible AI guidelines.

• Solid grasp of AI and machine learning concepts, with experience in NLP or chatbots.
• Experience crafting and iterating prompts, including few‑shot examples and output formatting techniques.
• Familiarity with embedding models, vector databases, and unstructured data processing.
• Building and consuming RESTful APIs, microservices, and handling JSON or XML data formats.
• Knowledge of data structures and algorithms such as lists, dictionaries, trees, and graphs for efficient agent design.
• Strong debugging and problem‑solving skills, able to distinguish between model and code issues.
• Comfortable working in sprints, collaborating across teams, and communicating technical needs.
• Quick learner who can adapt to new industry concepts for tailored agent solutions.
• Attention to detail and quality with consideration of edge cases, proper data handling, and thorough testing.
• Awareness of ethical considerations, including bias, confidentiality, and flagging questionable requests.

• Experience with AI model APIs such as OpenAI or Azure OpenAI, and ML frameworks like PyTorch or Tensor Flow.
• Hands‑on with Lang Chain or similar frameworks for prompt management and agent logic.
• Working knowledge of SQL, No
  
  SQL, and vector databases (e.g., Pinecone, Weaviate) for data retrieval.
• Familiarity with Docker, CI/CD, and cloud deployment on AWS, Azure, GCP, or serverless functions.
• Proficiency with Git and Dev Ops platforms (Git Hub, Git Lab, Bitbucket).
• Experience with testing tools such as PyTest, Postman, and AI evaluation methods.
• Knowledge of cloud AI services, event‑driven messaging (Rabbit
  
  MQ, Kafka, SQS), and logging solutions (Cloud Watch, Application Insights).
• Optional familiarity with UI frameworks like Streamlit or basic web development for internal demos.
• Understanding of security and compliance libraries for regulated industries.

$115,000 – $155,000 per year

Troy, MI