Senior Software Engineer (AI)

Role Overview
We are looking for a Senior AI/ML Engineer — Generative AI & Agentic Systems to design, develop, and productionize enterprise-grade Generative AI, RAG, and Agentic AI solutions.
The candidate will work closely with the AI Architect / Technical Lead to translate business requirements into scalable AI solutions and will be responsible for hands-on implementation, integration, evaluation, optimization, and deployment.
This role is ideal for an engineer who enjoys building real-world AI applications using LLMs, RAG pipelines, AI Agents, tool calling, vector databases, orchestration frameworks, and cloud technologies.
Key Responsibilities
Design and develop production-ready Generative AI and LLM-based applications.
Build scalable Retrieval-Augmented Generation (RAG) pipelines using embeddings, vector databases, reranking, retrieval, and contextual generation.
Develop Agentic AI workflows using frameworks such as LangGraph and LangChain.
Implement multi-agent workflows involving planning, reasoning, tool calling, delegation, memory, and orchestration.
Integrate LLMs from OpenAI, Anthropic, Google Gemini, and other providers.
Develop backend services and AI APIs using Python, FastAPI, and REST APIs.
Design and implement LLM evaluation frameworks to measure accuracy, relevance, groundedness, hallucination, latency, and other quality metrics.
Implement AI guardrails, validation, safety controls, structured outputs, and responsible AI practices.
Work with PostgreSQL, vector databases, and graph databases to build AI knowledge systems.
Containerize and deploy AI applications using Docker and cloud platforms such as Azure/AWS.
Optimize LLM applications for performance, scalability, reliability, and cost.
Collaborate with architects, frontend/backend engineers, DevOps, and business stakeholders.
Participate in technical design, code reviews, troubleshooting, and production support.
Stay current with emerging developments in LLMs, Agentic AI, RAG, open-source models, and AI infrastructure.
Must-Have Skills
Programming & Backend
Strong hands-on experience with Python
FastAPI
REST API development
Backend application architecture and development
Generative AI & LLM
LLM application development
RAG architecture and implementation
Prompt engineering
Embeddings and semantic search
Vector databases
LLM integration and orchestration
Experience with one or more of:
OpenAI
Anthropic
Google Gemini
Agentic AI
Hands-on experience building AI Agents
LangGraph and/or LangChain
Tool/function calling
Agent workflows and orchestration
Multi-agent systems
Agent state and memory management
Data & Infrastructure
PostgreSQL
Vector databases
Docker
Azure and/or AWS
API integration and microservices
AI Quality & Security
LLM evaluation
RAG evaluation
Hallucination detection/mitigation
AI guardrails
Structured output and schema validation
Understanding of AI security and responsible AI practices
Preferred / Good-to-Have Skills
Neo4j / GraphRAG
Model Context Protocol (MCP)
vLLM
Ollama
Open-source LLMs such as Llama, Qwen, Mistral, etc.
LoRA / parameter-efficient fine-tuning
Model fine-tuning
Kubernetes
CI/CD and Azure DevOps/GitHub Actions
React / Next.js
Redis or other caching technologies
Experience with cloud-based AI/ML infrastructure
Experience optimizing inference performance and LLM costs
What We Are Looking For
Strong problem-solving and analytical skills.
Ability to convert business requirements into practical AI solutions.
Strong understanding of LLM architecture and modern GenAI patterns.
Ability to write clean, maintainable, production-quality code.
Comfortable working in a fast-moving AI engineering environment.
Ability to independently investigate new AI technologies and implement POCs/prototypes.
Good understanding of software engineering principles, APIs, databases, security, and deployment.
Strong communication and collaboration skills.
Ability to work closely with an AI Architect / Technical Lead while taking ownership of implementation.

Work arrangement
No