AI Lead

BIGFORMULA Solutions Private Limited; Ernakulam; On-site; INR 4,000,000 - 6,500,000; Full time

Job summary

BIGFORMULA Solutions Private Limited invites an accomplished AI Lead with 5+ years to drive design, development and deployment of next‑generation AI solutions for real‑world problems.

You will lead end-to-end architecture, craft Agentic AI systems, and oversee production‑grade backend services using Python, FastAPI, REST APIs and containers on Azure. You will mentor engineers and help shape the company’s AI strategy.

Qualifications

• 5+ years hands-on experience delivering AI/ML solutions.
• Strong Python, FastAPI and backend architecture.
• Experience with Azure APIM and enterprise API architecture.
• Experience with LLMs, RAG and agentic AI.
• Proven track record delivering end-to-end AI projects.

Responsibilities

• Lead end‑to‑end architecture and delivery of AI solutions, from problem definition to production deployment.
• Design and implement production‑grade Agentic AI systems, including tool calling and orchestration.
• Develop scalable backend services using Python, FastAPI, REST APIs and microservices.
• Design, configure and manage Azure APIM with authentication, rate limiting, monitoring.
• Drive improvements by analyzing existing AI applications and leading deployment using Docker, Kubernetes/AKS, CI/CD.
• Mentor AI/ML and backend engineers and contribute to AI strategy and roadmap.

Skills

Machine Learning

Generative AI

Agentic AI

Python

FastAPI

REST APIs

Microservices

Azure Cloud

Docker

Kubernetes

CI/CD

MLOps

Education

Bachelor’s degree in Computer Science or related field

Master’s preferred

Tools

Azure API Management (APIM)

Docker

Kubernetes/AKS

CI/CD pipelines

Job description

We are seeking a highly accomplished AI Lead with 5+ years of industry experience to lead the design, development, and deployment of next-generation AI solutions for complex, real-world problems.

The ideal candidate will be a hands-on technical lead with strong expertise in Machine Learning, Generative AI, Agentic AI, backend engineering, and cloud architecture, with proven experience taking AI solutions from concept to production.

Key Responsibilities

• Lead the end-to-end architecture and delivery of AI solutions, from problem definition and POCs to production deployment.
• Design and implement production-grade Agentic AI systems, including agent orchestration, tool calling, RAG, memory, workflows, multi-agent systems, and human-in-the-loop.
• Develop scalable backend services using Python, FastAPI, REST APIs, and microservices.
• Design, configure, and manage Azure API Management (APIM), including authentication/authorization, JWT/Entra ID, API policies, rate limiting, throttling, routing, monitoring, and versioning.
• Analyze existing AI applications, identify architecture, performance, scalability, security, and integration issues, and drive technical improvements.
• Lead deployment and productionization using Docker, Kubernetes/AKS, CI/CD, Azure cloud services, and GPU infrastructure.
  Own production operations including monitoring, logging, tracing, alerting, performance optimization, troubleshooting, and incident resolution.
• Lead architecture and code reviews, technical POCs, engineering standards, and mentor AI/ML and backend engineers.
  Evaluate emerging AI technologies and contribute to the organization’s AI strategy and technical roadmap.

Qualifications & Experience

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; Master’s preferred.
• 5+ years of hands-on experience delivering AI/ML solutions, with strong knowledge of ML, Deep Learning, NLP, Generative AI, and Agentic AI.
• Proven experience delivering end-to-end AI projects from concept to production.
• Strong hands-on experience with Python, FastAPI, REST APIs, microservices, and backend architecture.
• Strong experience with Azure API Management (APIM) and enterprise API architecture.
• Strong experience with LLMs, RAG, Transformers, prompt engineering, fine-tuning, embeddings, and vector databases.
• Hands-on experience designing Agentic AI architectures, including tool calling, orchestration, memory, workflows, and multi-agent systems.
• Hands-on experience with Docker, Kubernetes/AKS, CI/CD, Azure cloud, and production AI deployments.
• Experience with MLOps, monitoring, observability, scalability, and production troubleshooting.
• Strong technical leadership, communication, problem-solving, and mentoring skills.