Lead System Engineer - AWS IAM, Python and Agentic AI

EPAM Systems; India; On-site; INR 2,000,000 - 2,800,000; Full time

Job summary

EPAM Systems is seeking a Lead System Engineer in India to define the strategic direction for next-generation secure AI systems. As a leader, you will architect solutions for agentic AI environments, focusing on security, compliance, and mentoring engineers.

Qualified candidates will have deep expertise in AWS IAM and Python, with experience in cloud security and multi-account AWS environments. Your role will involve leading architectural discussions and collaborating across teams to ensure secure cloud implementations.

Qualifications

• 8+ years of professional experience in system engineering and cloud security.
• Deep expertise in AWS IAM and Amazon AWS Security.
• Strong background in Amazon Bedrock AgentCore and AI Agents Frameworks.

Responsibilities

• Lead the architecture of secure-by-design controls for AI systems.
• Establish enterprise-wide strategies to address data leakage.
• Mentor and coach engineers, fostering technical growth.

Skills

AWS IAM

Python

Cloud Security

AI & ML Strategy

Network Security

Leadership

Communication

Tools

AWS Security Hub

Amazon Bedrock

GuardDuty

CloudTrail

Job description

We are looking for a Lead System Engineer with deep expertise in AWS IAM, Python, and Agentic AI to define the strategic direction and architect next-generation secure AI systems at enterprise scale. In this role, you will lead the design of secure-by-design controls for agentic mesh AI environments, establish governance frameworks across multi-account AWS landscapes, and drive the adoption of policy-aware AI agents operating within defined security and compliance boundaries. You will also mentor engineers, shape engineering standards, and act as a trusted advisor to senior stakeholders.

Responsibilities

• Lead the architecture and implementation of secure-by-design controls for agentic mesh AI systems built on Amazon Bedrock
• Define and own trust boundaries between autonomous AI agents and services across the enterprise
• Drive the assessment and mitigation of risks related to prompt injection, model misuse, and agent-to-agent trust and verification
• Establish enterprise-wide strategies to address data leakage and cross-agent contamination across AI workloads
• Define the vision and roadmap for policy-aware AI agents operating within security and compliance constraints
• Set standards for network security patterns for AI workloads, including VPC design, private endpoints, and Bedrock access controls
• Architect, govern, and continuously evolve multi-account AWS environments leveraging Organizations and Control Tower
• Define and oversee account isolation strategies for AI workloads, data, and agent execution
• Establish enforcement frameworks using AWS Security Hub, GuardDuty, Config, and CloudTrail
• Lead cross-functional collaboration with AI engineers, cloud teams, and governance stakeholders to align on security architecture and drive consensus on key decisions
• Mentor and coach senior and mid-level engineers, fostering technical growth and a security-first culture
• Represent the engineering organization in executive-level discussions, producing high-quality architectural documentation and communicating complex security concepts to both technical and non-technical audiences
• Contribute to pre-sales activities, technical assessments, and strategic initiatives as a subject matter expert

Requirements

• 8-12 years of general IT experience, including 8+ years of professional experience in system engineering and cloud security
• At least 1 year of relevant leadership experience
• Deep expertise in AWS IAM, Amazon AWS Security, and AWS Security Hub
• Advanced proficiency in Python for automation, security tooling, and framework development
• Strong background in Amazon Bedrock AgentCore and AI Agents Frameworks
• Solid knowledge of AI & ML Strategy with a focus on secure deployment patterns at enterprise scale
• Proven experience designing and governing multi-account AWS environments using Organizations and Control Tower
• Hands‑on expertise with AWS security services, including GuardDuty, Config, and CloudTrail
• Strong understanding of network security patterns for AI workloads, including VPC design and private endpoints
• Demonstrated ability to lead architectural decisions, mentor engineers, and influence stakeholders across organizational boundaries
• Structured thinker with a security‑first mindset, strong leadership presence, and excellent communication skills
• Written and spoken proficiency in English (B2 level or higher)

Nice to have

• Deep understanding of agentic AI concepts and design principles
• Hands‑on experience with multi‑agent systems architecture
• Practical knowledge of tool‑using and autonomous agents
• Experience contributing to industry communities, publications, or open‑source projects in the AI/cloud security space