Overview
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 Responsibilitie
s
Define and own end-to-end architecture for Generative AI applications deployed natively on A
WSLead technology decisions aroun
d:AWS Bedrock models and agent desi
gnOrchestration using AWS Strands S
DKIntegration patterns (sync, async, event-drive
n)Establish standards fo
r:Prompt engineeri
ngAgent workflo
wsModel lifecycle manageme
ntReview designs and code to ensure performance, scalability, and maintainabili
tyGenerative AI Solution Delive
ryLead hands-on development o
f:GenAI services, agents, and APIs using Pyth
onBedrock Agent Core SDK–based applicatio
nsGuide teams o
n:Prompt optimization and guardrai
lsCost-efficient token usa
geLatency and throughput optimizati
onDrive adoption of RAG, embeddings, and vector storage patterns where appropria
teAWS-Native Cloud Engineeri
ngDesign secure, scalable AWS architectures usin
g:AWS Lambda, ECS, EKS, E
C2S3, DynamoDB, Aurora, OpenSear
chAPI Gateway / A
LBDefine IAM, networking, and security patterns aligned with Zero Trust and least privile
geEnsure high availability, fault tolerance, and disaster recovery strategi
esDevOps, CI/CD & Platform Engineeri
ngDefine and enforce CI/CD standards for GenAI workloads usin
g:AWS CodePipeline / CodeBuild / CodeDepl
oyGitHub Actions / GitLab
CILead Infrastructure-as-Code initiatives usin
g:AWS CDK / CloudFormation / Terrafo
rmAutomate testing, deployment, rollback, and environment promoti
onObservability, Reliability & Operatio
nsOwn production observability strategy across AI and application layer
s:CloudWatch logs, metrics, dashboar
dsAWS X-Ray distributed traci
ngCustom metrics for AI behavior, latency, cost, and accura
cyDefine and monitor SLAs, SLOs, and error budge
tsLead incident response, RCA, and continuous improveme
ntSecurity, Governance & Responsible
AIEnsure secure and compliant GenAI implementation
s:Data encryption (at rest/in transi
t)Secrets manageme
ntSecure prompt and data handli
ngDefine guardrails fo
r:Data priva
cyPrompt injection ris
ksModel misuse and hallucinatio
nsAlign AI implementations with enterprise governance and compliance framewor
ksTeam Leadership & Stakeholder Manageme
ntMentor and guide developers and senior enginee
rsConduct design reviews, code reviews, and technical worksho
psCollaborate wit
h:Classification: Intern
alProduct manage
rsSecurity and compliance tea
msPlatform and data engineering tea
msTranslate business requirements into scalable technical solutio
nsRequired Skills & Qualificatio
nsCore Technical Skills (Must Hav
e)Expert-level Python developme
ntStrong hands-on experience wit
h:AWS Bedro
ckAWS Bedrock Agent Core S
DKAWS Strands S
DKDeep expertise in AWS cloud-native architectu
reCI/CD, DevOps automation, and Infrastructure as Co
deStrong observability and production operations experien
ce