Lead AI Engineer (S04)

About US:

Systango Technologies Limited (NSE: SYSTANGO) is a digital engineering company that offers enterprise-class IT and product engineering services to different size organizations. At Systango, we have a culture of efficiency - we use the best-in-breed technologies to commit quality at speed and world-class support to address critical business challenges. We leverage Gen AI, AI/Machine Learning and Blockchain to unlock the next stage of digitalization for traditional businesses. Our handpicked team is adept at web & enterprise development, mobile apps, QA and DevOps. Sila, Cuentas, Youtility, Porsche, MGM Grand, Deloitte, Grindr, and Tawk.to are some of the top clients that have entrusted us to enhance their digital capabilities and build disruptive innovations. We believe in making the impossible, possible and we do it literally.

About the Role

We are looking for a Lead AI Engineer with a strong software engineering background using Python/Java/NodeJS and hands-on experience building production-grade AI applications. The ideal candidate has spent the last 3–4 years designing and deploying GenAI solutions using LLMs, Retrieval-Augmented Generation (RAG), and AI agent frameworks.

You will lead the architecture and development of AI-powered products, working closely with Product, Engineering, and Data teams to deliver scalable, enterprise-ready AI solutions.

Key Responsibilities

• •Design, build, and deploy end-to-end AI applications powered by commercial and open-source LLMs.
• •Develop scalable Retrieval-Augmented Generation (RAG) pipelines using enterprise data sources and vector databases.
• •Design and implement AI agents and multi-agent workflows for business automation and intelligent decision-making.
• •Integrate AI capabilities with backend services, APIs, databases, and enterprise applications.
• •Build scalable Python services and APIs to serve AI workloads.
• •Evaluate and optimize AI applications for quality, latency, reliability, and cost.
• •Deploy, monitor, and continuously improve AI applications in production.
• •Mentor engineers and contribute to AI architecture, engineering standards, and technical best practices.

Required Skills

Software Engineering

• •8–10 years of overall experience in software development.
• •Strong understanding of software architecture, distributed systems, API design, and engineering best practices.
• •Experience building production services using FastAPI or similar frameworks.

Generative AI

• •3–4 years of experience building production GenAI or LLM-based applications.
• •Experience with commercial and/or open-source LLMs such as OpenAI, Claude, Gemini, Llama, or Mistral.
• •Strong hands-on experience building RAG applications.
• •Experience with vector databases such as Pinecone, Weaviate, pgvector, Chroma, or FAISS.
• •Experience designing and implementing agentic AI systems, including orchestrator agents, multi-agent architectures, and agent-to-agent collaboration using frameworks and protocols such as LangGraph, OpenAI Agents SDK, Gemini ADK, Pydantic AI, and A2A Protocols.
• •Strong understanding of prompt engineering, structured outputs, tool/function calling, and AI workflows.

Cloud & Infrastructure

• •Experience with AWS, Azure, or GCP.
• •Docker, Kubernetes, and CI/CD for AI applications.
• •Experience deploying and operating AI applications in production.

Databases

PostgreSQL, MySQL, MongoDB, or DynamoDB.

Nice to Have

• •Experience fine-tuning open-source LLMs using LoRA, QLoRA, PEFT, or the Hugging Face ecosystem.
• •Experience deploying and managing AI agents at enterprise scale.
• •Hands-on experience with Amazon Bedrock, Google Vertex AI / Gemini Enterprise, Azure AI Foundry, or similar enterprise AI platforms.
• •Experience with AI evaluation and observability frameworks such as RAGAS, DeepEval, TruLens, LangSmith, or similar.
• •Familiarity with PyTorch, TensorFlow, or custom model development.
• •Experience building AI solutions for enterprise or regulated industries.