[Remote] Senior Engineer - Agentic AI
Note: The job is a remote job and is open to candidates in USA. Tata Consultancy Services is seeking a Senior Engineer specializing in Agentic AI. In this hands-on development role, you will build and deploy AI agent solutions, working closely with clients to deliver cutting-edge applications that utilize large language models and advanced prompt engineering.
Responsibilities
- 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 (e.g., APIs, web search, databases)
- Prompt Engineering & Optimization: Craft, refine, and test prompts to guide agent behavior, including fallback strategies for uncertainty
- Implement RAG 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 (e.g., travel booking APIs, payment gateways), handling formatting, RESTful calls, and data responses as needed
- 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 (Docker, cloud), 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
Skills
- BACHELOR OF COMPUTER SCIENCE
- 8 - 25 Years of experience
- Expertise in Python (and optionally Java, JavaScript, or C#)
- Unit testing and version control (Git)
- Solid grasp of machine learning and AI concepts
- Experience with NLP or chatbots
- Experience crafting and iterating prompts
- Familiarity with embedding models, vector databases, and unstructured data processing
- Building and consuming RESTful APIs
- Knowledge of lists, dictionaries, trees/graphs, and their application in efficient agent design
- Strong troubleshooting abilities to distinguish between model and code issues
- Comfortable working in sprints, collaborating across teams, and communicating technical needs
- Ability to quickly learn new industry concepts for tailored agent solutions
- Consideration of edge cases, proper data handling, and thorough testing
- Recognize bias, confidentiality issues, and flag questionable requests
- Mastery of Python for AI/ML
- Exposure to JavaScript/TypeScript, FastAPI, or Flask for APIs
- Experience with AI model APIs (OpenAI, Azure OpenAI)
- Experience with ML frameworks like PyTorch or TensorFlow
- Hands-on with LangChain or similar frameworks for prompt management and agent logic
- Working with SQL, NoSQL, and vector databases (e.g., Pinecone, Weaviate) for data retrieval
- Familiarity with Docker, CI/CD, and cloud deployment (AWS, Azure, GCP, Lambda/Functions)
- Proficient with Git and DevOps platforms (GitHub, GitLab, Bitbucket)
- Experience with PyTest, Postman, and AI evaluation methods
- Practical knowledge of cloud AI offerings and environment configuration
- Implementing logging (Python logging, CloudWatch, Application Insights) for tracking and debugging
- Experience with event-driven workflows (RabbitMQ, Kafka, SQS)
- Familiarity with Streamlit or basic web development for internal agent demos
- Handling OAuth, encryption, and compliance libraries for regulated industries
- Using NLP libraries for text preprocessing and embeddings (e.g., sentence-transformers, Jupyter notebooks)
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