Role Overview:
The Team Lead – AI is a (Senior Software Engineer level) role responsible for leading the design, development, and delivery of AI-powered automation solutions across the EMR/EHR ecosystem. The role combines strong hands-on AI engineering capability with technical leadership, solution ownership, and day-to-day guidance of AI automation resources. The ideal candidate is a strong individual contributor who can lead technical execution, translate business problems into scalable AI solutions, review solution quality, mentor team members, and work closely with Product, Engineering, QA, DevOps, and business stakeholders to deliver secure and measurable AI automation.
Key Responsibilities:
- Lead the design and implementation of AI-powered automation workflows for product and business teams.
- Own technical delivery of AI assistants, copilots, intelligent workflows, and agent-based automation solutions.
- Design and integrate Large Language Models (LLMs) into internal and customer-facing applications.
- Provide hands-on development using Python, REST APIs, JSON, webhooks, LangChain, LangGraph, AWS Bedrock, and n8n.
- Lead solution design for Retrieval-Augmented Generation (RAG), AI agents, prompt engineering, and multi-step workflow orchestration.
- Review code, prompts, workflows, integrations, and technical designs to ensure quality, scalability, security, and maintainability.
- Break down AI initiatives into executable technical tasks, guide team members, and track delivery against agreed timelines.
- Mentor AI engineers and support capability development through technical guidance, code reviews, and knowledge sharing.
- Collaborate with Product and business stakeholders to identify, assess, and prioritize high-impact automation opportunities.
- Build and oversee API-based integrations between AI platforms, enterprise applications, and third-party systems.
- Evaluate emerging AI tools, frameworks, and models and recommend technologies based on business fit, security, cost, and scalability.
- Monitor AI solution performance, output quality, latency, reliability, and adoption, and drive continuous optimization.
- Ensure AI implementations comply with organizational security, data privacy, governance, and healthcare technology requirements.
- Develop reusable AI components, engineering standards, technical documentation, and implementation best practices.
- Support conversational AI and voice automation initiatives, including Amazon Connect (AWS Connect) where applicable.
- Create or define dashboards and metrics to measure automation impact, productivity gains, adoption, and reduction in manual effort.
Functional Success Metrics
- On-time and successful delivery of AI automation initiatives.
- Quality, reliability, and maintainability of AI solutions delivered by the team.
- Reduction in manual effort and process turnaround time through automation.
- Accuracy and consistency of AI-generated outputs.
- Stability and performance of APIs, workflows, and enterprise integrations.
- Adoption and measurable business impact of AI-powered tools.
- Effective technical guidance, code review, and capability development of team members.
- Compliance with security, privacy, governance, and engineering standards.
- Stakeholder satisfaction with AI solution delivery and responsiveness.
- Reusable, well-documented AI components and technical standards.
Functional Success Metrics:
- 4–6 years of software engineering experience, including hands-on experience in AI engineering, AI automation, or intelligent workflow development.
- Strong proficiency in Python and backend/API development.
- Hands-on experience with Large Language Models (LLMs), Prompt Engineering, and production AI integrations.
- Strong experience with LangChain, LangGraph, AWS Bedrock, and n8n.
- Experience designing or implementing AI agents, Retrieval-Augmented Generation (RAG), and multi-step AI workflows.
- Experience building and consuming REST APIs, webhooks, JSON-based integrations, and third-party services.
- Working knowledge of AWS services; experience with Amazon Connect (AWS Connect), Lambda, and S3 is preferred.
- Strong understanding of Git, code review practices, secure API development, and Agile delivery.
- Experience providing technical guidance, mentoring engineers, reviewing technical work, or leading delivery of small engineering initiatives.
- Strong analytical, problem-solving, stakeholder communication, and ownership skills.
- Experience in Healthcare IT, EMR/EHR, or SaaS products is preferred.
Key Competencies:
| Technical | Behavioral |
|---|---|
| Python & Type Script | Analytical Thinking |
| AI & Large Language Models (LLMs) | Problem Solving |
| Prompt Engineering | Innovation |
| LangChain & LangGraph | Technical Leadership |
| AWS Bedrock | Ownership & Accountability |
| n8n Workflow Automation | Adaptability |
| AI Agents & Multi-Agent Workflows | Communication Skills |
| Retrieval-Augmented Generation (RAG) | Collaboration |
| REST API Development & Integration | Stakeholder Management |
| JSON & Webhooks | Coaching & Knowledge Sharing |
| AWS Cloud Fundamentals | Continuous Learning |
| Amazon Connect (AWS Connect) | Attention to Detail |
| Git, Code Review & Version Control | Customer Focus |
| Secure AI / API Development |
Why Join Us?
- Get a chance to contribute and get recognition from Day 1
- Work 5 days a week (Enjoy work-life balance)
- Modern work environment
- A friendly, Supportive, Professional, and achievement-oriented management team
- Competitive Salary and Benefits, professionally run HR team
- An opportunity to learn new things every day
Why Join Us?
Perks & Benefits:
- Market Competitive Salary.
- Fuel Allowance.
- Medical OPD & IPD
- Health Insurance.
- Provident Fund.
- Paid Leaves.
- EOBI.
- Public Holiday Allowance.
- Employee Referral Bonus.
- Annual Salary Reviews.
