Staff Architect

Summit Consulting Services; Ernakulam; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

Summit Consulting Services is seeking a Staff Architect to drive architecture across both an internal AI engineering platform and client-facing product systems. This role combines hands-on design, code contribution, and leading reviews while mentoring other senior engineers to establish durable enterprise patterns.

You will move between platform and product problems, shaping scalable, secure systems that integrate AI capabilities across services, data, and developer experience in a regulated

Qualifications

• 11+ years of professional software engineering experience with leadership at staff level or equivalent.
• Proven track record designing and shipping production systems built on LLMs or autonomous agents.
• Strong ability to mentor senior engineers and drive cross-team technical initiatives.

Responsibilities

• Lead reviews, architecture decision records and technical writing for the org.
• Mentor staff and senior engineers across teams; guide tradeoffs and architectural decisions.
• Collaborate with security, compliance and product teams to ensure scalable, secure AI workflows.
• Shape architecture across platform and client-facing products, including APIs and integrations.
• Drive observability, reliability and multi-tenancy in distributed AI-enabled systems.

Skills

LLM systems

Distributed systems

Architecture leadership

Mentoring staff

Tools

AWS

CI/CD

Job description

We are looking for a Staff Architect to help drive architecture across two connected pillars at organisation: the internal AI engineering platform that accelerates how teams build, and the client-facing product architecture that our customers depend on every day. This is a hands‑on, deeply collaborative technical leadership role for someone who has shipped real systems with LLMs and agents, who is comfortable shaping architecture across services, data, security and developer experience, and who is energized by working through other engineers rather than around them.

The Role

You will help drive the technical direction of organisation's AI engineering platform and the architecture of our client-facing products. That means partnering with engineering leads, product, security and operations to shape the systems that internal teams build on, the products customers rely on and the AI capabilities that increasingly run through both. You will write code, write design docs, lead reviews, mentor other senior and staff engineers and turn good local decisions into durable enterprise patterns.

This role is intentionally cross‑cutting. You will move between platform problems (how engineers and product managers ship faster and more consistently across the company) and product problems (how our client‑facing systems scale, integrate, stay secure and incorporate AI in ways that hold up in a regulated industry).

Key Responsibilities

Internal AI Engineering Platform

• Help drive the architecture of organisation's internal AI scaffolding platform, including agent orchestration, skill and contract design, multi‑IDE adapters (Claude Code, Cursor, Codex and successors) and the developer experience that ties them together.
• Co‑design enterprise‑wide standards for building with LLMs and agents: prompt and context patterns, retrieval and grounding, tool integration, evals, guardrails, cost and latency budgets, observability and incident response.
• Partner with engineering leads across product teams to evolve their stacks toward shared scaffolding rather than parallel reinvention, and contribute reusable skills, templates and adapters back to the platform.
• Help shape the evaluation strategy for AI features: how we measure quality, regressions, safety and business impact, and how evals are wired into CI, staging and production telemetry.
• Influence model selection, agent framework choices, vendor versus in‑house tradeoffs and where to place the boundaries between platform and product code.
• Partner with product engineering leads to drive the architecture of organisation's client‑facing systems across the surfaces customers interact with, including web applications, APIs, integrations and embedded AI features.
• Shape the service architecture: domain boundaries, service decomposition, design platform services, AI services and event‑driven patterns.
• Contribute to the data architecture in close collaboration with the Data Architect: how transactional, analytical and regulatory data flows through products, how contracts are defined between systems, how lineage and quality are preserved.
• Help drive the AI in product strategy: where LLMs, RAG, agents and assistive features belong in customer‑facing workflows, how they are evaluated, how they fail gracefully and how their behavior is auditable.
• Shape choices around scalability, performance, multi‑tenancy and resilience for client workloads, including capacity planning, caching, rate limiting, async processing and graceful degradation.
• Co‑design the security and compliance posture for products in a regulated domain: authentication, authorization, tenancy isolation, encryption, secrets handling, audit logging and data residency.
• Influence observability and operability standards: telemetry, logging, tracing, SLOs, on‑call ergonomics and incident review.
• Guide integration and interoperability decisions across customer integrations, third‑party services, data feeds and partner platforms.

Technical Leadership Across Both Pillars

• Lead and contribute to design reviews, architecture decision records and technical writing that sets the bar for the broader engineering organization.
• Mentor staff and senior engineers across teams. Coach them through hard tradeoffs rather than making the calls for them.
• Be the technical voice that helps leadership decide what to build, what to buy and what to retire, and that translates technical reality back to business stakeholders.
• Work with security, compliance and risk to make sure AI‑driven workflows and product features meet ORAGANISATION's obligations around data handling, auditability, access control and regulatory exposure.
• Stay close to the broader industry. Bring back practices that are working elsewhere and adapt them to our context.
• 11+ years of professional software engineering experience, with a clear track record of technical leadership at staff level or equivalent cross‑team scope.
• Demonstrated experience designing and shipping production systems built on LLMs or autonomous agents. You can speak in detail to systems you architected, the tradeoffs you made and what you would do differently.
• Strong distributed systems and software architecture background. You can move fluently between service design, API design, data flow, security and developer experience.
• Hands‑on experience architecting client‑facing SaaS or enterprise products: service boundaries, APIs, integrations, multi‑tenancy, performance, resilience and observability.
• Working understanding of data architecture: storage choices (relational, document, analytical, vector), data contracts and how product systems and data platforms meet at the boundary.
• Hands‑on fluency with modern AI engineering practice: prompt and context engineering, retrieval augmented generation, agent orchestration, tool use, evals and guardrails.
• Experience leading cross‑team technical initiatives through influence in a mid to large engineering organization. You can move a group of senior engineers toward shared decisions without relying on positional authority.
• Strong written and verbal communication. You can write a one‑page design doc that aligns a room of senior people and a five‑line summary that aligns an executive.
• A pragmatic, collaborative mindset. You balance rigor with delivery, work inside legacy constraints and still move the architecture forward.

Nice to Have

• Experience building developer tooling or internal platforms at enterprise scale, especially scaffolding, code generation, workflow automation or developer productivity systems.
• Experience integrating AI assistants (Claude Code, Cursor, Codex, GitHub Copilot or similar) into team workflows as a deliberate engineering practice, not just individual use.
• Familiarity with MCP‑style tool integration, agent contracts and multi‑agent orchestration patterns.
• Experience with eval frameworks (LangSmith or commercial/in‑house equivalents) and with observability for LLM and agent systems in production.
• Experience designing for compliance, audit and regulatory requirements in financial services, healthcare or another regulated, data‑sensitive domain.
• Familiarity with cloud‑native architecture on AWS (or equivalent), containerization, IaC and modern CI/CD.
• A track record of writing or speaking publicly about software architecture or AI engineering practice.

What We Offer

• A senior technical leadership role with scope across both the AI platform that internal teams build on and the products our customers rely on.
• The chance to help define the architectural standards and patterns that hundreds of engineers and product managers will use every day.
• A collaborative, forward‑thinking team that takes both engineering rigor and emerging AI practice seriously.
• The opportunity to work at the intersection of regulated financial data and modern AI tooling, where the technical bar and the business stakes are both high.