AI Engineer Lead

Solverminds Solutions & Technologies Pvt Ltd; Chennai; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Solverminds Solutions & Technologies Pvt. Ltd in Chennai (Siruseri) seeks aSenior AI Engineer to act as technical lead for the Agentic AI product engineering pod. This hybrid IC/lead role combines hands-on coding with day-to-day technical guidance, task allocation, and junior engineer growth.

You will own design reviews, establish engineering standards, and collaborate with product to translate requirements into scalable AI agent capabilities.

Qualifications

• Strong ML foundation with tokenization, context windows, embeddings, and transformers.
• Hands-on production AI agent design patterns: ReAct, planning, memory, and tool use.
• Deep experience with RAG frameworks and LangChain/LangGraph or AutoGen in product dev.
• Azure AI services for agent orchestration (Azure AI Foundry, Prompt Flow, Azure OpenAI).
• Advanced prompt and context engineering with robust eval strategies for nondeterministic outputs.

Responsibilities

• Lead delivery of production AI agent systems from prototyping to deployment.
• Lead design and code reviews to maintain engineering quality and standards.
• Directly manage 1-2 junior engineers: 1:1s, feedback, and growth support.
• Write clean, well-tested Python code (FastAPI, Pydantic, async).
• Unblock the team on technical issues and escalate to management when needed.
• Document engineering best practices for system design, prompts, and evaluation.

Skills

ML fundamentals

Agent design patterns

RAG frameworks

LangChain

LangGraph

AutoGen

Azure AI services

Prompt engineering

Evaluation methodology

Python

Tools

Azure OpenAI Service

Prompt Flow

Neo4j

LangChain tooling

Job description

Solverminds Solutions & Technologies Pvt. Ltd | Full time

Chennai Siruseri, India | Posted on 01/07/2026

We are looking for aSenior AI Engineer to act as the technical lead for our Agentic AI productengineering pod. This is a hybrid IC/lead role. Beyond remain deeply hands-on,this role is responsible for owning the day-to-day technical guidance, taskallocation, growth of junior engineers into the domain and upholdingengineering standards.

KeyResponsibilities

• Leadthe delivery of production AI agent systems, from prototyping agent workflowsto deploying and scaling them in production.
• Leaddesign and code reviews for the pod, ensuring consistent engineering qualityand technical standards.
• Directlymanage 1-2 junior engineers: assign and prioritize work, run regular 1:1s, giveongoing feedback, and support their career growth.
• Writeclean, maintainable, well-tested Python code (FastAPI, Pydantic, async) and setthe standard for code quality across the team.
• Unblockthe team on technical issues and act as the first escalation point beforeinvolving the engineering manager.
• Establishand document engineering best practices for system design, prompt/contextstrategies, and evaluation methodology.
• Driveevaluation standards for non-deterministic LLM outputs across the team (evaldesign, regression testing, red teaming).
• Partnerdirectly with product and business stakeholders to translate ambiguousrequirements into scalable agent system design.
• Evaluatefrontier and open-source LLMs, agent frameworks, and tooling; make and defendadoption recommendations to leadership.

Requirements

RequiredSkills & Experience

• Strongmachine learning foundation, including deep understanding of tokenization,context windows, embeddings, and transformer architectures.
• Hands-onproduction experience with agent design patterns (ReAct, planning, reflection,tool use, memory, multi-agent handoff).
• Deephands-on experience with RAG frameworks, LangChain/LangGraph or AutoGen forproduct development, including A2A and MCP integration at scale.
• Hands-onexperience with Azure AI services for agent orchestration (e.g. Azure AIFoundry, Prompt Flow, Azure OpenAI Service).
• Advancedexperience in prompt and context engineering, with a track record of drivingeval methodology and testing strategy for non-deterministic outputs across ateam.

Software Engineering

• 5years of experience in Python product development, with deep proficiency in frameworks/libraries.
• Experienceowning cost/latency tradeoffs and optimization for LLM systems at productionscale.
• Experienceusing AI coding assistants (e.g. Cursor, Claude Code) in daily developmentworkflows.

Technical Leadership

• Experienceleading design/code reviews and setting technical standards for a team.
• Comfortablemaking and defending technical tradeoffs to non-technical stakeholders andleadership.
• Experiencementoring engineers, with genuine interest in growing junior talent.
• Abilityto break down and delegate work appropriately based on team members' skilllevel.
• Comfortablegiving direct, constructive feedback and running regular 1:1s.
• Strongcollaboration skills with product, engineering, and domain experts to translatebusiness requirements into agent capabilities.

Goodto Have

• Knowledgegraph (KG) experience, including hands-on work with Neo4j, with the ability toapply KG patterns in agent grounding contexts.
• Hands-onexperience fine-tuning open-source LLMs, particularly with parameter-efficientmethods (LoRA/QLoRA) and/or supervised fine-tuning (SFT); exposure to RLHF orDPO is a plus.

WhatSuccess Looks Like in This Role

• ProductionAI agent systems are delivered reliably, with sound architecture that scales asusage grows.
• Thejunior engineers on the pod grow in capability, autonomy, and confidence underthis person's mentorship.
• Theteam maintains high, consistent engineering standards across code, design, andevaluation practices.
• Leadershiptrusts this person's technical judgment on architecture, tooling, and frameworkdecisions.