Job Description

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

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.