Title: Generative AI Technical Lead-App Development
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
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