AI / ML Lead

About the Role

We are looking for an experienced

AI / ML Lead

to define and execute the AI / ML strategy, with a strong focus on developing and deploying advanced models tailored to

insurance use cases . You will lead the model lifecycle end-to-end, integrate GenAI / LLM solutions, and ensure governance and compliance in a regulated industry.

This is a

founding-level opportunity

to : Shape the foundation

of a next-gen insurtech platform.

Collaborate with a highly motivated team tackling

real-world, high-impact challenges .

Design elegant, scalable systems that set new benchmarks for the industry.

Drive meaningful innovation in a space that is

ripe for disruption .

Key Responsibilities

Define and drive the

AI / ML strategy .

Design and implement

native model integration frameworks .

Build

scalable, objective-centric ML solutions

for insurance applications (fraud detection, risk assessment, underwriting, claims automation).

Lead end-to-end

ML lifecycle management

— data preprocessing, model training, deployment, monitoring, and optimization.

Develop and fine-tune

LLMs (GPT, Claude, LLaMA)

with expertise in

prompt engineering, RAG architectures, and evaluation frameworks .

Integrate ML models with

enterprise applications

(Java / Spring) via REST APIs.

Deploy and manage models in

containerized environments

(Kubernetes, Docker).

Establish governance for

responsible AI : bias detection, explainability (LIME / SHAP), fairness metrics, and regulatory compliance.

Implement

drift detection, automated monitoring, versioning, and A / B testing

for continuous improvement.

Required Skills & Experience

6+ years

of hands-on experience in ML engineering and model lifecycle management.

Strong expertise in

Python development

(FastAPI, TensorFlow, PyTorch, Scikit-learn, XGBoost).

Proficiency in

ML model deployment, versioning, A / B testing, and Kubernetes containerization .

Hands-on experience with

document processing, OCR, NLP pipelines, and vector databases .

Proven ability to build and optimize

LLMs and Generative AI solutions

(fine-tuning, quantization, model optimization).

Familiarity with

RAG pipelines, prompt engineering, and GenAI evaluation techniques .

Deep knowledge of

model governance , including explainable AI, fairness metrics, and bias detection.

Experience in integrating ML solutions with

enterprise systems .

Preferred Domain Expertise

Insurance industry experience in :

Fraud detection

Risk assessment

Underwriting models

Claims automation

AI regulatory compliance

What’s in it for You

The chance to be part of a

founding-level tech team .

End-to-end ownership of

AI / ML initiatives in a high-impact domain .

Opportunities to work on

cutting-edge Generative AI and ML solutions .

A collaborative, high-growth environment where your work will create

real-world impact .

Competitive compensation and benefits.