Location: Noida Berger Tower, India
Thales is a global technology leader trusted by governments, institutions, and enterprises to tackle their most demanding challenges. From quantum applications and artificial intelligence to cybersecurity and 6G innovation, our solutions empower critical decisions rooted in human intelligence. Operating at the forefront of aerospace and space, cybersecurity and digital identity, we’re driven by a mission to build a future we can all trust.
Present in India since 1953, Thales is headquartered in Noida and has other operational offices and sites spread across Delhi, Gurugram, Bengaluru and Mumbai, among others. Over 2200 employees are working with Thales and its joint ventures in India. Since the beginning, Thales has been playing an essential role in India’s growth story by sharing its technologies and expertise in Defence, Aerospace and Cyber & Digital sectors. Thales has two engineering competence centres in India - in Noida focused on Cyber & Digital business, while the in Bengaluru focuses on hardware, software and systems engineering capabilities for both the civil and defence sectors, serving global needs. The Group has also established an MRO (Maintenance, Repair & Overhaul) facility in Gurugram to provide comprehensive avionics maintenance and repair services to Indian airlines and support the growth of the local aviation industry.
Position Summary
The System Architect, based in Noida, will define the technical vision and target architecture for secure, scalable IAM platforms and AI-native engineering capabilities. The role combines deep systems architecture expertise with hands-on leadership in agentic AI, AI coding agents, and modern software delivery.
The architect will design identity capabilities for workforce, customer, partner, machine, workload, and AI-agent identities, covering authentication, authorization, governance, adaptive access, threat detection, and secure delegation.
The role will lead AI-native practices across architecture, development, testing, security, deployment, and operations. The successful candidate must use and govern AI coding agents in real engineering workflows and design agentic systems with bounded autonomy, traceability, and enterprise-grade quality, security, privacy, and compliance.
Essential Functions / Key Areas of Responsibility
- Own the target architecture and roadmap for IAM and AI-enabled platforms, aligned with business strategy, Zero Trust, privacy, security, and responsible AI.
- Architect identity, lifecycle, credential, authorization, delegation, governance, audit, and threat-detection capabilities for human and non-human identities.
- Design agentic AI systems that plan, use tools, collaborate, and execute multi-step workflows within defined security and operational boundaries.
- Define guardrails for agent identity, least privilege, human approval, tool access, runtime isolation, context, observability, auditability, and safe failure.
- Lead AI-native engineering across requirements, architecture, coding, testing, reviews, documentation, deployment, and operations.
- Use AI coding agents for repository analysis, implementation, refactoring, testing, debugging, code review, documentation, and delivery automation.
- Govern AI-assisted development through approved-tool controls, data protection, output validation, secure review, provenance, and traceability.
- Translate business outcomes into reference architectures, decision records, quality attributes, service objectives, and implementation guardrails.
- Architect resilient cloud-native, distributed, event-driven, and API-first systems with strong production readiness and cost efficiency.
- Lead architecture reviews, threat modeling, technical discovery, proofs of concept, build-versus-buy analysis, and cross-functional decisions.
- Partner with product, engineering, security, data, operations, compliance, and legal teams to deliver secure, auditable, resilient solutions.
- Mentor architects and engineers and produce clear, reusable architecture guidance, threat models, diagrams, evaluations, and runbooks.
Minimum Requirements: Skills, Experience, Education, Technical/Specialized Knowledge, Certifications, Language
- 12+ years designing and delivering complex software platforms, with substantial architecture, technical leadership, and cross-functional delivery responsibility.
- 7+ years in IAM across customer or workforce identity, federation, SSO, MFA, password less access, lifecycle governance, privileged access, and fine-grained authorization.
- Minimum requirement: hands-on experience designing and building agentic AI solutions using planning, tool invocation, retrieval, context or memory, multi-step workflows and human or policy controls.
- Minimum requirement: hands-on, day-to-day use of AI coding agents for repository analysis, implementation, refactoring, testing, debugging, reviews, documentation, or delivery automation.
- Experience governing AI-generated code through human review, automated testing, security scanning, secrets and dependency checks, provenance, and auditability.
- Strong generative AI knowledge covering models, prompt and context engineering, retrieval, model and tool selection, evaluation, observability, cost, and responsible AI.
- Practical understanding of agent risks, including prompt injection, excessive agency, insecure tool use, data leakage, identity spoofing, supply-chain compromise, and unsafe actions.
- Strong experience with cloud-native, distributed, multi-tenant systems, APIs, asynchronous messaging, containers, infrastructure as code, automated delivery, and observability.
- Deep IAM knowledge, including OAuth, OpenID Connect, SAML, SCIM, FIDO2/WebAuthn, passkeys, PKI, workload identity, secrets, and policy-based authorization.
- Strong system-design fundamentals across domain and API design, resilience, consistency, scalability, performance, security, privacy, data architecture, and operations.
- Hands-on capability across modern programming ecosystems, quality engineering, threat modeling, technical specifications, architecture decisions, and reference implementations.
- Proven ability to influence stakeholders, lead technical decisions, mentor engineers, and align product, engineering, security, and operations.
- Bachelor’s or Master’s degree in a relevant discipline, or equivalent practical experience.
- Strong written and spoken English communication skills.
Preferred Qualifications
- Experience architecting identity, authorization, delegation, and governance for AI agents and other non-human identities.
- Experience with secure agent-to-tool and agent-to-agent integration, including Model Context Protocol or equivalent approaches.
- Experience with specification-driven development, reusable AI workflows, and organization-wide AI-assisted engineering adoption.
- Experience evaluating, red-teaming, monitoring, and responding to incidents involving generative or agentic AI systems.
- Experience with AI-enabled identity or security capabilities, including adaptive access, behavioral analytics, threat detection, fraud, risk scoring, or identity proofing.
- Experience designing model-agnostic AI platforms, enterprise knowledge integration, reusable agents, and cost-aware model routing.
- Experience with software and AI supply-chain security, regulated platforms, or contributions to architecture communities, standards, publications, or open source.
At Thales, we’re committed to fostering a workplace where respect, trust, collaboration, and passion drive everything we do. Here, you’ll feel empowered to bring your best self, thrive in a supportive culture, and love the work you do. Join us, and be part of a team reimagining technology to create solutions that truly make a difference – for a safer, greener, and more inclusive world.
