Experience: 4-8 Years
Responsibilities
We are seeking a
Senior Agentic AI Engineer with 4+ years of experience in
Generative AI, AWS cloud deployment, and enterprise agent orchestration. This role will drive the
Enterprise Agent Factory initiative, building production‑ready agent frameworks, registries, and orchestration pipelines for large‑scale enterprise AI programs.
Key Responsibilities
Architect and implement
multi‑agent orchestration frameworks (Orchestrator/Supervisor agents, A2A agents with enterprise service integrations).
Build reusable
agent registries for custom agents across multiple tenants and cloud environments.
Define
Human‑in‑the‑Loop and Human‑on‑the‑Loop patterns for enterprise workflows.
- Cloud & Production Deployment
Lead
AWS AgentCore development and migration (Dev/QA/Prod environments).
Deploy
LLMaaS and QAaaS services on AWS with focus on scalability, automation, and bug‑free production rollout.
Integrate agents into enterprise portals and applications (e.g., dashboards, workflow orchestration tools, analytics platforms).
Enhance
AI guardrails, documentation, and compliance frameworks for regulated industries.
Define
AI testing strategies and standards for enterprise validation.
Strengthen monitoring foundations across
API gateways, event streaming platforms, container orchestration, observability tools, and backend services.
Establish
baseline health metrics (latency, throughput, error rates, uptime).
Implement
failure visibility and alerting protocols across integration layers.
Drive modernization of
QAaaS platform across AWS, distributed databases, and parser integrations.
Explore advanced
GenAI techniques (adaptive prompting, retrieval‑augmented generation, multi‑modal agents).
Collaborate with cross‑functional teams to onboard new services into the
enterprise AI foundation.
Preferred Qualifications
Background in
regulated industries or enterprise AI delivery.
Experience with
QA automation and LLM‑based validation metrics.
Knowledge of
data privacy, security, and enterprise risk mitigation.
Requirements
Required Skills & Experience
4+ years in AI/ML engineering, with
3+ years in GenAI/LLM projects.
Strong expertise in
AWS cloud services (SageMaker, Bedrock, ECS/EKS, Lambda).
Hands‑on experience with
LLM frameworks (LangChain, Lyzr, RAG pipelines).
Proven track record of
production‑level deployments in enterprise environments.
Familiarity with
multi‑agent orchestration and agent factory concepts.
Strong knowledge of
Python, APIs, microservices, CI/CD pipelines.
Experience in
enterprise governance, compliance, and monitoring frameworks.
Excellent communication skills to distill technical achievements into
executive‑ready messaging.
We offer
- Opportunity to work on bleeding-edge projects
- Work with a highly motivated and dedicated team
- Competitive salary
- Flexible schedule
- Benefits package - medical insurance, sports
- Corporate social events
- Professional development opportunities
- Well-equipped office
About Us
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.
