AI Agentic Engineer

Job description

Must Have Technical / Functional Skills

Core Engineering & Programming

• Strong software engineering fundamentals with expert-level proficiency in Python. Experience with Java, Go, or TypeScript is a strong plus.

LLM & GenAI Application Development

• Proven, hands-on experience building and deploying production-grade applications using Large Language Models (LLMs) like GPT, Claude, or Gemini.
• This must go beyond simple API calls and include experience with tool/function-calling, structured outputs, and evaluation.

Agentic AI Frameworks & Orchestration

• Demonstrable expertise in designing and implementing agentic workflows using frameworks like LangGraph, Semantic Kernel, AutoGen, or similar.
• Experience with multi-agent systems, planning, and autonomous execution is critical.

RAG (Retrieval-Augmented Generation)

• Deep, practical knowledge of building and optimizing RAG pipelines. This includes data ingestion, various chunking strategies, embeddings, vector databases (e.g., Pinecone, Chroma, FAISS), and hybrid search/reranking.

Production & MLOps

• Experience with production engineering practices, including building scalable APIs (REST, RPC), microservices, CI/CD pipelines, containerization (Docker, Kubernetes), and cloud platforms (AWS, Azure, or GCP). Roles & Responsibilities

Agentic System Design & Engineering

• Architect, build, and deploy advanced AI agents capable of autonomous reasoning, decision-making, and self-directed task execution. Design and implement complex, multi-step agentic workflows that integrate with enterprise APIs, data sources, and platforms.

RAG and Grounding Implementation

• Develop robust RAG pipelines to ground agent responses in factual, reliable data. This includes managing the full lifecycle from data ingestion and vectorization to retrieval and citation.

Tooling and Integration

• Build and maintain the "tools" that agents use to interact with the digital world. Create secure, well-documented tool interfaces for internal services, databases, and third-party APIs.

Evaluation, Guardrails & Safety

• Design and implement comprehensive evaluation frameworks to measure agent performance, accuracy, and reliability.
• Develop and enforce safety guardrails, policy checks, and fallback mechanisms to ensure agents operate safely and predictably in production environments.

Optimization and Productionization

• Debug, monitor, and optimize agentic systems for latency, cost, and efficiency. Own the end-to-end deployment process, including CI/CD, structured logging, and incident response for AI systems. Generic Managerial Skills, If any

Problem-Solving & Critical Thinking

• Ability to analyze complex, ambiguous problems and design innovative, practical solutions. Thrives in navigating the uncertainty inherent in emerging AI technologies.

Collaboration & Communication

• Excellent communication skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders. Proven experience working cross-functionally with product, research, and infrastructure teams.

Ownership & Leadership

• A bias for action and a strong sense of ownership.

Capable of driving projects from conception to completion, mentoring junior engineers, and helping to define and influence AI strategy and best practices Base Salary Range : $100,000 to $120,000 Per Annum TCS Employee Benefits Summary: Discretionary Annual Incentive.

Comprehensive Medical Coverage

Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.

Family Support

Maternal & Parental Leaves.

Insurance Options

Auto & Home Insurance, Identity Theft Protection.

Convenience & Professional Growth

Commuter Benefits & Certification & Training Reimbursement.

Time Off

Vacation, Time Off, Sick Leave & Holidays.

Legal & Financial Assistance

Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing. #LI-SV2 #LI-KUMARAN </div

Qualifications

BACHELOR OF COMPUTER SCIENCE