Role Overview :

The Tech Lead will be responsible for leading the design, architecture, development, and delivery of next-generation AI and Generative AI solutions. The role involves driving innovation, mentoring engineering teams, and transforming AI Proof of Concepts into enterprise-grade production systems.

The ideal candidate should possess strong expertise in AI/LLM technologies, cloud-native development, full-stack engineering, and modern software architecture.

Key Responsibilities (KRA) :

1. AI Product Architecture & Technical Leadership :

- Lead the end-to-end design and development of AI/GenAI products and intelligent agents.

- Define technical architecture, coding standards, and engineering best practices.

- Drive technical decision-making and ensure scalable, secure, and maintainable solutions.

- Collaborate with business stakeholders to translate requirements into technical solutions.

2. Generative AI & LLM Solutions Development :

- Design and implement GenAI applications using OpenAI, Azure OpenAI, and other LLM platforms.

- Build RAG (Retrieval Augmented Generation) based solutions.

- Develop agentic workflows and AI-powered automation solutions.

- Optimize prompts, model performance, and response quality.

3. Cloud & Enterprise Solution Engineering :

- Build and deploy cloud-native applications on Microsoft Azure.

- Utilize Azure Functions, Service Bus, Document Intelligence, and related Azure services.

- Ensure high availability, scalability, security, and performance of applications.

- Establish CI/CD and deployment best practices.

4. Product Innovation & Delivery :

- Drive innovation initiatives and identify opportunities to leverage AI across business functions.

- Convert Proof of Concepts (POCs) into production-ready enterprise solutions.

- Evaluate emerging AI technologies and recommend adoption strategies.

- Ensure timely delivery of projects while maintaining quality standards.

5. Team Leadership & Mentoring :

- Lead and mentor a team of software engineers and AI developers.

- Conduct code reviews, technical assessments, and architecture reviews.

- Guide mid-level engineers in software design and AI implementation.

- Foster a culture of innovation, collaboration, and continuous learning.

6. Data & Knowledge Management :

- Design vector database architectures for semantic search and knowledge retrieval.

- Work with SQL and NoSQL databases including PostgreSQL and MongoDB.

- Implement efficient data pipelines supporting AI applications.

- Manage data security, governance, and compliance requirements.

Technical Skills Required:

Core Technologies:

- C#

- .NET Core

- Angular

- Python

AI / GenAI Technologies:

- OpenAI

- Azure OpenAI

- Large Language Models (LLMs)

- Retrieval Augmented Generation (RAG)

- Agentic AI Frameworks

- Prompt Engineering

Cloud Technologies:

- Microsoft Azure

- Azure Functions

- Azure Service Bus

- Azure Document Intelligence

Databases:

- PostgreSQL

- MongoDB

- SQL

- NoSQL

AI Ecosystem & Tools:

- Microsoft Copilot Studio

- Power Automate

- Vector Databases

- Haystack

- LangChain

- Streamlit

- MLOps Fundamentals

Preferred Candidate Profile:

- Proven experience leading engineering teams and enterprise-scale product delivery.

- Strong hands-on development background with .NET and Python.

- Experience in shipping AI/GenAI solutions from concept to production.

- Excellent understanding of cloud architecture and distributed systems.

- Strong stakeholder management and communication skills.

- Experience working in global delivery environments.

- Role: Technical Lead

- Industry Type: BPM / BPO

- Department: Engineering - Software & QA

- Employment Type: Full Time, Permanent

- Role Category: Software Development

Education:

- UG: B.Tech / B.E. in Any Specialization