Senior AI Tech Lead

Strong hands-on capability in Python, TypeScript/JavaScript, REST APIs, microservices, event-driven patterns,

and containerized deployments.

Experience with AWS Bedrock, SageMaker, Lambda, Step Functions, ECS/EKS, API Gateway, S3, CloudWatch,

and CI/CD tooling

Python, TypeScript/JavaScript, REST APIs, microservices, Event-driven patterns, AWS Bedrock, SageMaker, Lambda,

Step Functions, ECS/EKS, API Gateway, S3, CloudWatch, prompt engineering, agent orchestration, tool integration,

Vector stores, embeddings, model evaluation, and AI guardrails, AI agent capabilities, API layers, RAG services,

tool connectors

Strong hands-on capability in Python, TypeScript/JavaScript, REST APIs, microservices, event-driven patterns, and containerized deployments.

Experience with AWS Bedrock, SageMaker, Lambda, Step Functions, ECS/EKS, API Gateway, S3, CloudWatch, and CI/CD tooling.

Deep understanding of prompt engineering, agent orchestration, tool integration, vector stores, embeddings, model evaluation, and AI guardrails.

Ability to enforce engineering standards, code quality, secure coding, performance tuning and observability practices.

Strong leadership, mentoring, estimation, planning, and stakeholder communication skills.

Familiarity with compliance, audit logging, model risk controls, and responsible AI practices.

Responsibilities

Lead technical delivery of AI agent capabilities, reusable platform components, integrations and automation workflows.

Translate solution architecture into detailed engineering designs, sprint plans, and implementation tasks.

Guide developers on AI patterns, cloud-native implementation, secure coding, testability & performance optimization.

Build and review core components such as agent orchestration services, API layers, RAG services, tool connectors, and model interaction modules.

Coordinate with architects, product owners, UX designers, security SMEs, and QA to drive end-to-end delivery.

Establish technical best practices, coding standards, review processes, and reusable accelerators.

Support environment readiness, deployment planning, defect triage, production readiness reviews & knowledge transition.

Generic Qualifications

Bachelor's degree in Computer Science Engineering, Data Science, or related discipline; advanced degree preferred.

10+ years of software engineering experience with 3+ years in AI/ML, Gen AI, or intelligent automation delivery.

Hands-on experience building LLM-based applications, AI agents, RAG pipelines, APIs & cloud-native services.

Experience leading engineering teams in agile delivery models for enterprise-scale platforms.

Strong exposure to AWS cloud services and modern DevSecOps practices.

Insurance or financial services technology delivery experience preferred.