Lead Python Engineer

Theomnihire; Chennai; On-site; INR 4,500,000 - 7,500,000; Full time

Job summary

Theomnihire in Chennai is seeking a highly experienced Python Lead to drive architecture, backend development, and AI-enabled product delivery. This player-coach role blends hands-on engineering with technical leadership, evaluating new ideas, building PoCs, and guiding a 3–6 engineer team to production success.

The ideal candidate has 10+ years in software, strong GenAI experience, and expertise with LLMs, RAG, embeddings, vector databases, and agent workflows, plus cloud, Docker, and CI/CD

Qualifications

• 10+ years of overall software engineering experience.
• 6+ years of hands-on production experience with Python 3.x.
• Strong experience with FastAPI, Django, or Flask and REST API development.
• Experience designing and delivering at least two production systems end to end.
• Proven experience in technical feasibility studies and PoCs.
• Strong practical knowledge of AI/GenAI and LLM-based application development.
• Hands-on experience with RAG architectures and implementation.
• Hands-on experience building AI Agents / Agentic AI workflows, including tool/function calling, orchestration, and multi-step task execution.
• Experience integrating LLM APIs such as OpenAI, Anthropic, or equivalent providers.
• Strong understanding of embeddings, vector search, semantic search, chunking, retrieval strategies, and vector databases.
• Ability to design and implement production-ready AI applications with accuracy, latency, scalability, security, cost, and observability.
• Strong database knowledge: PostgreSQL or MySQL, plus Redis or MongoDB.
• Experience with Celery / RQ or equivalent task queues and RabbitMQ / Kafka / SQS.
• Production experience with AWS / Azure / GCP, Docker, and CI/CD.
• Hands-on experience with pytest, code quality tools, and Python type checking.
• Knowledge of application security, OAuth2 / JWT, OWASP Top 10, and access control.
• At least 2 years of experience leading 3+ engineers.
• Strong communication, problem-solving, estimation, and delivery ownership skills.

Responsibilities

• Conduct technical feasibility studies, PoCs, and build-versus-buy evaluations.
• Prepare feasibility reports with effort estimates, costs, risks, and go/no-go recommendations.
• Design scalable, secure, and maintainable Python applications, REST APIs, and AI-enabled backend systems.
• Develop backend services using Python and frameworks such as FastAPI, Django, or Flask.
• Design and implement GenAI/LLM-powered applications, RAG pipelines, and AI Agents.
• Evaluate and integrate LLMs and AI services such as OpenAI, Anthropic, or equivalent platforms.
• Design AI application architecture including prompt orchestration, embeddings, vector search, retrieval pipelines, tool/function calling, and agent workflows.
• Own application architecture, code quality, performance optimization, and production releases.
• Work with PostgreSQL / MySQL, Redis / MongoDB, task queues, message brokers, and vector databases.
• Manage cloud deployments, Docker, CI/CD pipelines, monitoring, and production operations.
• Lead, mentor, and guide a team of engineers.
• Drive code reviews, sprint planning, technical documentation, and engineering best practices.
• Collaborate with the Founder / CTO and stakeholders to ensure timely product delivery.
• Stay current with emerging AI technologies and identify opportunities to leverage AI/automation to improve product capabilities and engineering efficiency.

Skills

Python engineering

AI/GenAI expertise

LLM integration

Team leadership

System architecture

REST API design

Performance optimization

Communication

Tools

FastAPI

Django

Flask

PostgreSQL

MySQL

Redis

MongoDB

Celery/RQ

RabbitMQ/Kafka/SQS

Docker

CI/CD

AWS/Azure/GCP

Kubernetes

Terraform

Prometheus

Grafana

OpenAI API

Anthropic API

Job description

Joining Preference: Immediate joiners or candidates with a very short notice period

About the Role

We are looking for a highly experienced, hands-on Python Lead / Lead Python Engineer to drive technical feasibility, application architecture, backend development, AI-enabled solutions, and end-to-end product delivery.

This is a player-coach role combining hands-on Python engineering with technical leadership. You will evaluate new product ideas, build proof of concepts (PoCs), make architecture decisions, lead a team of engineers, and take applications from feasibility to production.

The ideal candidate should also have strong practical knowledge of AI/GenAI technologies, including LLM integrations, RAG architectures, vector databases, and AI Agent development , and be capable of evaluating and implementing AI-driven product capabilities.

Key Responsibilities

Conduct technical feasibility studies, PoCs, and build-versus-buy evaluations.

Prepare feasibility reports with effort estimates, costs, risks, and go/no-go recommendations.

Design scalable, secure, and maintainable Python applications, REST APIs, and AI-enabled backend systems.

Develop backend services using Python and frameworks such as FastAPI, Django, or Flask.

Design and implement GenAI/LLM-powered applications, RAG pipelines, and AI Agents .

Evaluate and integrate LLMs and AI services such as OpenAI, Anthropic, or equivalent platforms.

Design AI application architecture including prompt orchestration, embeddings, vector search, retrieval pipelines, tool/function calling, and agent workflows .

Own application architecture, code quality, performance optimization, and production releases.

Work with PostgreSQL / MySQL, Redis / MongoDB, task queues, message brokers, and vector databases.

Manage cloud deployments, Docker, CI/CD pipelines, monitoring, and production operations.

Lead, mentor, and guide a team of 3–6 engineers.

Drive code reviews, sprint planning, technical documentation, and engineering best practices.

Collaborate with the Founder / CTO and stakeholders to ensure timely product delivery.

Stay current with emerging AI technologies and identify opportunities to leverage AI/automation to improve product capabilities and engineering efficiency.

Requirements

Mandatory Skills

10+ years of overall software engineering experience.

6+ years of hands-on production experience with Python 3.x.

Strong experience with FastAPI, Django, or Flask and REST API development.

Experience designing and delivering at least two production systems end to end .

Proven experience in technical feasibility studies and PoCs.

Strong practical knowledge of AI/GenAI and LLM-based application development.

Hands-on experience with RAG (Retrieval-Augmented Generation) architectures and implementation.

Hands-on experience building AI Agents / Agentic AI workflows , including tool/function calling, orchestration, and multi-step task execution.

Experience integrating LLM APIs such as OpenAI, Anthropic, or equivalent providers .

Strong understanding of embeddings, vector search, semantic search, chunking, retrieval strategies, and vector databases .

Ability to design and implement production-ready AI applications with appropriate considerations for accuracy, latency, scalability, security, cost, and observability .

Strong database knowledge: PostgreSQL or MySQL, plus Redis or MongoDB.

Experience with Celery / RQ or equivalent task queues and RabbitMQ / Kafka / SQS.

Production experience with AWS / Azure / GCP, Docker, and CI/CD.

Hands-on experience with pytest, code quality tools, and Python type checking.

Knowledge of application security, OAuth2 / JWT, OWASP Top 10, and access control.

At least 2 years of experience leading 3+ engineers .

Strong communication, problem-solving, estimation, and delivery ownership skills.

Good-to-Have Skills

Applied cryptography, key management, and secure licensing mechanisms.

Kubernetes, Terraform, Prometheus, Grafana, and OpenTelemetry.

Performance optimization using Rust, Cython, or Go.

Experience taking products from concept to production and first customers.

Experience with advanced agentic AI patterns such as multi-agent systems, MCP, workflow orchestration, AI tool integration, and autonomous task execution .

Experience with AI evaluation, observability, guardrails, prompt/version management, and LLM cost optimization.

What We Are Looking For

We are looking for a strong hands-on technical leader who can move seamlessly between Python engineering, system architecture, AI/GenAI implementation, technical feasibility, and team leadership .

The right candidate should be comfortable taking an idea from concept → feasibility → PoC → architecture → development → AI integration → production deployment , while making sound technical and business-oriented decisions along the way.