Lead Software & Systems Architect AIRE

Role

Lead Software & Systems Architect (Expert)

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About the UNIT/ Unit Overview 

AIRE (AI-native Requirements Engineering) is a new BMW Group tool for managing vehicle requirements, the descriptions of what a car and its software must do. It keeps the full history of every requirement, shows how requirements are linked to each other and to tests, and shows what is affected when something changes. It helps teams meet automotive standards such as Automotive SPICE and ISO 26262. AIRE is built for AI agents first and a user interface later, and the team uses AI agents to help build it. In this role you design the overall structure of AIRE and make the key technical decisions.

Location

Pune / Bangalore

Experience

Minimum of ten years of software engineering experience, including at least four years in a lead or principal architecture role for data-intensive systems.

Number of openings

1

What awaits you/ Job Profile 

• Own the target architecture and its documentation (arc42, C4, ADRs). Decide and document the open architecture decisions, for example storage technology, graph store, branching model and deployment platform, based on prototypes and measured evidence.

• Design the bitemporal, append-only core model, including revision checksums, time travel, baselines and the semantics of branching and three-way merge.

• Define the CQRS split between the relational source of truth and the graph read index, including synchronisation, consistency guarantees and rebuild strategies.

• Define the domain-action architecture together with the Senior Agent & Domain Action Engineer: typed contracts, idempotency, error semantics, authorisation hooks, approval gates and audit events. Ensure that agents never access the database directly.

• Translate quality goals into automated fitness functions and architecture checks in CI, and make them part of the definition of done.

• Write and maintain architecture specifications and agent instructions so that coding agents implement consistently with the architecture. Review architecturally significant agent-generated changes as the accountable human.

• Build reference implementations and spikes for high-risk areas such as concurrency, bitemporal queries and large-scale traversal.

• Ensure that the architecture supports conformity evidence for Automotive SPICE and ISO 26262 tool qualification, together with the Functional Safety & Process Compliance Specialist.

• Identify and manage technical risks and technical debt, and advise the Lead Value Flow Engineer on feasibility, sequencing and cost.

• Design the production architecture for security, performance and operability, and define the migration and cut-over architecture.

• Hand over architecture knowledge (ADRs, runbooks, agent skills) to the successor team before first production in 2028 Q3.

What should you bring along

• Degree in Computer Science, Software Engineering, Information Systems or a related field, or equivalent relevant experience.

• Minimum of ten years of software engineering experience, including at least four years in a lead or principal architecture role for data-intensive systems.

• Demonstrated track record of designing and delivering systems with demanding consistency, auditability and performance requirements.

• Proven ability to lead technically through influence and to make evidence-based architecture decisions.

Must have technical skill 

• Proven experience as lead or principal architect for data-intensive, distributed enterprise systems delivered to production.

• Deep knowledge of temporal data modelling, in particular bitemporal models (valid time and transaction time), append-only and event-sourced storage, revision checksums and time-travel queries.

• Strong command of CQRS, polyglot persistence, consistency models, optimistic concurrency, transaction isolation and idempotent write paths.

• Experience designing graph-based traceability or dependency models, including traversal performance, impact propagation and the trade-offs between relational and native graph stores.

• Experience designing agent-first systems: typed, versioned domain contracts as the primary interface, least-privilege tool access for AI agents, approval workflows for risky operations, and complete audit trails.

• Ability to define measurable quality goals and fitness functions (for example traversal latency for 5–8 hops with 50 concurrent users, variant resolution times and data volumes of 100k to 1M objects) and to verify them automatically.

• Hands-on proficiency in Python (for example FastAPI) and PostgreSQL, with the ability to build reference implementations for critical paths.

• Practical use of AI-native engineering: writing architecture specifications, ADRs and constraints that coding agents follow, and reviewing agent-generated designs and code critically.

• Solid understanding of cloud architecture on Microsoft Azure, including private networking, managed identities, container platforms and managed databases.

Good to have technical skills

• Domain knowledge of automotive requirements engineering, ALM tools (Codebeamer, DOORS, Polarion), ReqIF and product line engineering with 150%/100% variant models.

• Knowledge of Automotive SPICE (SYS.1–5, SWE.1–6), ISO 26262 (including tool qualification in Part 8) and ISO/IEC/IEEE 29148.

• Experience with semantic branching and record-level three-way merge of structured data.

• Experience with graph databases (for example Neo4j, FalkorDB, Apache AGE) and with ontology standards such as RDF/OWL and ISO/IEC 21838.

• Experience with arc42, C4 and architecture decision records in a docs-as-code workflow.

• Familiarity with BMW BASE (BMW Agentic Software Engineering), the Model Context Protocol (MCP) and BMW enterprise architecture governance.