Lead System Engineer - AWS IAM, Python and Agentic AI

EPAM Systems

Maharashtra

On-site

INR 3,000,000 - 6,000,000

Full time

4 days ago
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Job summary

EPAM Systems is seeking 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.

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 within security boundaries.

Qualifications

  • 8-12 years of general IT experience, incl. 8+ years 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 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 boundaries.
  • Security-first mindset with strong leadership and communication skills.
  • Written and spoken proficiency in English (B2 level or higher).

Responsibilities

  • Lead architecture and implementation of secure-by-design controls for agentic mesh AI systems on Amazon Bedrock.
  • Define and own trust boundaries between autonomous AI agents and services.
  • Drive risk assessment and mitigation for prompt injection, model misuse, and agent-to-agent trust.
  • Establish enterprise-wide strategies to prevent data leakage and cross-agent contamination.
  • Define vision and roadmap for policy-aware AI agents under security constraints.
  • Set standards for AI workload network security, including VPC design and private endpoints.
  • Govern multi-account AWS environments using Organizations and Control Tower.
  • Define 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.
  • Mentor and coach engineers, promoting security-first culture.
  • Represent engineering in executive discussions with clear architectural documentation.
  • Contribute to pre-sales, technical assessments, and strategic initiatives as SME.

Skills

Leadership
Security architecture
Mentoring
English proficiency

Tools

AWS IAM
AWS Security Hub
GuardDuty
Config
CloudTrail
Amazon Bedrock
Control Tower
Organizations

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
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