Generative AI Technical Lead-App Development

Overview

Long Description

Job Description

Generative AI Tech Lead (AWS-Native)

Location Hyderabad / Hybrid / Remote (as applicable)

Experience 8–15 years overall experience, with 3–5 years leading cloud and AI engineering teams

Role Summary - We are looking for a Generative AI Tech Lead to provide technical leadership and architectural direction for building and operating production-grade GenAI solutions on AWS. This role combines hands-on development, solution architecture, team mentorship, and operational ownership.

The Tech Lead will own end-to-end delivery of GenAI platforms using Python, AWS Bedrock (Agent Core SDK), AWS Strands SDK, and modern DevOps and observability practices, ensuring scalability, security, reliability, and cost efficiency.

Key Responsibilities

Define and own end-to-end architecture for Generative AI applications deployed natively on AWS

Lead Technology Decisions Around:

AWS Bedrock models and agent design

Orchestration using AWS Strands SDK

Integration patterns (sync, async, event-driven)

Establish Standards For:

Prompt engineering

Agent workflows

Model lifecycle management

Review designs and code to ensure performance, scalability, and maintainability

Generative AI Solution Delivery

Lead Hands-on Development Of:

GenAI services, agents, and APIs using Python

Bedrock Agent Core SDK–based applications

Guide Teams On:

Prompt optimization and guardrails

Cost-efficient token usage

Latency and throughput optimization

Drive adoption of RAG, embeddings, and vector storage patterns where appropriate

AWS-Native Cloud Engineering

Design Secure, Scalable AWS Architectures Using:

AWS Lambda, ECS, EKS, EC2

S3, DynamoDB, Aurora, OpenSearch

API Gateway / ALB

Define IAM, networking, and security patterns aligned with Zero Trust and least privilege

Ensure high availability, fault tolerance, and disaster recovery strategies

DevOps, CI/CD & Platform Engineering

Define And Enforce CI/CD Standards For GenAI Workloads Using:

AWS CodePipeline / CodeBuild / CodeDeploy

GitHub Actions / GitLab CI

Lead Infrastructure-as-Code Initiatives Using:

AWS CDK / CloudFormation / Terraform

Automate testing, deployment, rollback, and environment promotion

Observability, Reliability & Operations

Own Production Observability Strategy Across AI And Application Layers:

CloudWatch logs, metrics, dashboards

AWS X-Ray distributed tracing

Custom metrics for AI behavior, latency, cost, and accuracy

Define and monitor SLAs, SLOs, and error budgets

Lead incident response, RCA, and continuous improvement

Security, Governance & Responsible AI

Ensure Secure And Compliant GenAI Implementations:

Data encryption (at rest/in transit)

Secrets management

Secure prompt and data handling

Define Guardrails For:

Data privacy

Prompt injection risks

Model misuse and hallucinations

Align AI implementations with enterprise governance and compliance frameworks

Team Leadership & Stakeholder Management

Mentor and guide developers and senior engineers

Conduct design reviews, code reviews, and technical workshops

Collaborate With:

Classification: Internal

Product managers

Security and compliance teams

Platform and data engineering teams

Translate business requirements into scalable technical solutions

Required Skills & Qualifications

Core Technical Skills (Must Have)

Expert-level Python development

Strong Hands-on Experience With:

AWS Bedrock

AWS Bedrock Agent Core SDK

AWS Strands SDK

Deep expertise in AWS cloud-native architecture

CI/CD, DevOps automation, and Infrastructure as Code

Strong observability and production operations experience

Strong Hands-on Experience With:

AWS Bedrock

AWS Bedrock Agent Core SDK

AWS Strands SDK

Deep expertise in AWS cloud-native architecture

CI/CD, DevOps automation, and Infrastructure as Code

Strong observability and production operations experience