Product Development Engineer

Inspirisys; Chennai District; On-site; INR 350,000 - 800,000; Full time

Job summary

Inspirisys is seeking a senior engineering leader to drive product and technical strategy for a multi-tenant platform in India. You will co-own the roadmap with Product and Design, shaping what gets built and when to refactor or ship pragmatic fixes.

You will lead and scale the engineering organization, establish disciplines like sprint planning and incident response, and champion AI adoption across the product and development workflow to boost velocity and customer value.

Qualifications

• Strong hands-on software engineering with depth in at least one modern stack.
• Experience embedding AI/LLM systems, RAG, vector DBs, agentic tech.
• Cloud architecture across AWS/Azure/GCP with security focus.

Responsibilities

• Co-own product strategy and shape what gets built with design and product teams.
• Lead and scale the engineering org as the company grows.
• Define and mature DevOps, CI/CD, and infra-as-code practices.
• Own site reliability targets, incident response, and postmortems.
• Champion AI adoption and use AI-assisted development tools to boost velocity.
• Engage with stakeholders and manage engineering budget and vendor decisions.

Skills

Software engineering

AI/LLM systems

Cloud architecture

Microservices

APIs

Kubernetes

Security

Tools

Kafka

EventBridge

PubSub

Kubernetes

OAuth2

Zero Trust

Terraform

Job description

Product & Technical Strategy:

• Co-own product strategy with Product and Design shape what gets built, not just execute a handed-down roadmap.
• Drive the technical architecture for a scalable, multi-tenant product, with a clear point of view on when to refactor, rebuild, or ship the pragmatic fix.
• Own the balance between shipping fast for product-market fit and building a platform that won't collapse under scale.

AI & Innovation:

• Champion AI adoption on two fronts: (1) embedding AI/ML capabilities into the product where they create genuine customer value, and (2) using AI-assisted development tools (code gen, testing, code review, observability) to raise team velocity and quality.

People & Org:

• Lead and scale the engineering org (ICs, tech leads, managers) as the product and company grow, hiring ahead of need without over-hiring.
• Set up (or mature) engineering rituals: sprint planning, architecture review, incident response, on-call, postmortems.

DevOps, Infrastructure & Reliability:

• Own DevOps and infrastructure strategy — CI/CD pipelines, deployment automation, environment management (dev/staging/prod), and infrastructure-as-code.
• Drive site reliability practices: uptime/SLA targets, on-call rotations, incident response, root-cause analysis, and blameless postmortems.
• Own cloud cost management and infrastructure scaling decisions — right-sizing spend against growth stage.
• Oversee the observability stack — logging, monitoring, alerting, tracing — so issues are caught before customers feel them.
• Define disaster recovery and business continuity plans for production systems.

Security & Compliance:

• Set and enforce security practices across the SDLC: dependency management, secrets handling, access control, vulnerability scanning, and compliance needs (SOC 2 / ISO 27001 / GDPR as applicable).

Business & Stakeholders:

• Own engineering metrics that matter to a product company — deployment frequency, cycle time, defect escape rate, MTTR — and their connection to customer-facing outcomes (retention, NPS, uptime).
• Partner closely with Sales/CS/Support on customer escalations, technical due diligence for enterprise deals, and roadmap trade-offs.
• Manage engineering budget, tooling spend, and vendor/build-vs-buy decisions.
• Be a visible technical leader externally — conference talks, blog posts, or community presence that supports hiring and company brand (as relevant).

Core Technical Skills:

• Strong hands-on background in software engineering, with real depth in at least one modern stack (languages, frameworks, cloud).
• Experience with AI/LLM systems, RAG, vector DBs, and agentic frameworks.
• Cloud architecture (AWS/Azure/GCP) — compute, networking, security, serverless.
• Microservices, API gateways, event streaming (Kafka/EventBridge/PubSub).
• Databases: SQL, NoSQL, graph, vector.
• DevOps: CI/CD, containers, Kubernetes.
• Security: OAuth2, JWT, SSO, Zero Trust, data governance.

Architectural & Leadership Skills:

• Enterprise architecture frameworks (TOGAF, Zachman).
• Domain-driven design (DDD), event-driven architecture (EDA).
• High availability, scalability, resilience, disaster recovery.
• Cost modelling and performance engineering.
• A coaching mindset — measures success by the growth of the people around them as much as the systems they build.
• Comfortable as an internal evangelist and an external presenter/orator for the company's technical work.