AI/ML Engineer Agentic AI & LLM Systems

Role: AI/ML Engineer – Agentic AI & LLM Systems Function: Artificial Intelligence / Machine Learning Engineering Location: Bangalore, India (Onsite) Type: Full-time Industry: Information Technology & Services, Management Consulting About Company The company is a digital engineering firm founded in 2020 and headquartered in Tampa, Florida. It specializes in AI-driven digital transformation for enterprises. Over 450 professionals work across seven global offices, including Bangalore, Trivandrum, Toronto, Dallas, Belgrade, Johannesburg, and Bogota. The company has completed 55+ enterprise projects across 25+ countries. In 2023, it expanded its product engineering capabilities by acquiring a product engineering firm. It operates with a fast-paced, ownership-driven culture built on agility, client-centricity, and ethical execution. Position Overview This role sits at the intersection of applied AI research and production engineering. You will own the design and delivery of agentic AI systems and LLM-powered applications that solve real enterprise problems at scale. Responsibilities include architecting multi-agent pipelines, RAG systems, and LLM integrations — taking them from prototype to production. You will collaborate with data engineers, product managers, and domain experts across the company's global delivery network. The ideal candidate brings both depth in agent orchestration and the engineering rigor to ship reliable, observable AI systems. Role & Responsibilities Design and implement end-to-end RAG pipelines — including chunking strategies, vector store selection, retrieval optimization, and context injection — for production LLM applications Build and orchestrate multi-agent systems using LangChain, LangGraph, AutoGen, CrewAI, or Azure ADK, including agent reasoning loops, tool use, and inter-agent collaboration patterns Develop and maintain backend services in Java/Spring Boot to expose LLM capabilities as REST APIs and integrate with enterprise microservices Integrate LLMs from multiple providers (OpenAI, Anthropic, Meta/Llama) with robust prompt libraries, function-calling patterns, and fallback strategies for production reliability Design semantic storage layers using vector databases (Pinecone, Weaviate, Milvus, Chroma, or FAISS) and knowledge graphs for retrieval and reasoning Build evaluation frameworks and observability tooling to monitor agent performance, hallucination rates, latency, and cost across deployed systems Maintain code quality and technical documentation, and contribute to internal knowledge sharing on emerging agentic AI patterns and LLM best practices Must Have Criteria 4+ years of software development experience, with at least 1–2 years of hands-on experience building and deploying LLM-based or AI/ML systems in production Hands-on experience with LangChain and LangGraph for LLM application development, including RAG architecture design and implementation Proficiency with at least one agentic AI framework: AutoGen, CrewAI, or Azure ADK (Agent Development Kit) 3+ years of professional Java development with Spring Boot and Spring Framework, including REST API design and microservices architecture Practical experience integrating LLMs from providers such as OpenAI (GPT-4), Anthropic (Claude), or Meta (Llama), including prompt engineering and function-calling patterns Hands-on experience with vector databases — Pinecone, Weaviate, Milvus, Chroma, or FAISS — for semantic search and RAG pipelines Proficiency with Python for AI/ML scripting and development alongside Java-based backend work Nice to Have Experience with containerization (Docker) and orchestration (Kubernetes) for deploying AI workloads Familiarity with cloud platforms — AWS, Azure, or GCP — and serverless architectures for LLM serving Knowledge of LLM fine-tuning, transfer learning, or model optimization techniques Experience with CI/CD pipelines, monitoring, logging, or observability tools in an MLOps or LLMOps context Background in information retrieval, NLP, or classical machine learning; or contribution to open-source AI/ML projects What We Offer Direct ownership of agentic AI systems deployed across enterprise clients in 25+ countries Access to the latest LLM models, AI tooling, and infrastructure — with budget to experiment and ship Collaborative team of experienced AI/ML and platform engineers across the company's global delivery centers Onsite role in Bangalore with a high-growth, globally active engineering firm and a clear career growth trajectory