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 :

Agentic AI Development :

- 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).

Governance & Compliance :

- Enhance AI guardrails, documentation, and compliance frameworks for regulated industries.

- Define AI testing strategies and standards for enterprise validation.

Monitoring & Reliability :

- 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.

Innovation & Scaling :

- 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.