Engineering Head

Job Opening

Head of Engineering

Senior Leadership - 8+ Years Experience - AI-First Leader - Full-Time

Department: Engineering

Location: Pune

Experience: 8+ Years

Reports To: CTO

About 301io:

301io is a fast-moving technology company building next-generation software products for global markets. Our engineering team is the heartbeat of the company, and we believe that great software starts with great engineering leadership. We are a team that embraces AI not as a novelty, but as a core part of how we work and we are looking for an engineering leader who embodies that belief and can scale it across every team.

Role Overview:

The Head of Engineering is a senior leadership role that sits one level below the CTO and owns the full engineering organisation. You will carry responsibility for people, process, architecture, and delivery across four functions: Frontend Engineering, Backend Engineering, DevOps / Infrastructure, and QA. Beyond execution, you will be the cultural engine of the engineering org someone who instils an AI-first mindset in every engineer, establishes modern AI-assisted development practices, and ensures that the way 301io builds software is always ahead of the curve. You are equally comfortable whiteboarding a distributed systems architecture, setting standards for AI-assisted coding workflows, running a team retrospective, and presenting trade-offs to the CTO.

What we mean by AI-first:

AI-first does not mean using AI occasionally. It means your engineers reach for AI tools before they reach for Stack Overflow. It means prompting is a skill your team practices deliberately. It means you set standards for how AI-generated code is reviewed, tested, and trusted. It means you track where AI is saving time and where it is creating risk and you course-correct with data.

Leadership Pillars:

- AI-First Culture: Champion AI-assisted engineering across every team. You dont just tolerate AI tools you set the standard for how the organisation uses them to build better software, faster.

- People & Team Leadership: Hire, mentor, and build a high-performing engineering organisation. Create a culture where engineers grow, collaborate, and take pride in what they ship.

- Solution Architecture: Own technical design at the system level. Translate product ambitions into sound, scalable, and maintainable architectures that the whole team can build with confidence.

- Delivery & Execution: Drive reliable, predictable delivery across squads. Balance speed with quality, protect engineering bandwidth, and keep the roadmap on track without burning people out.

Key Culture & Engineering Excellence:

- Define and champion the companys AI-first engineering philosophy across all teams and functions.

- Set standards for AI-assisted development which tools to use, when to use them, and how to use them well.

- Establish best practices for coding with AI tools effective prompting, prompt chaining, context management, and code review of AI-generated output.

- Lead by example personally demonstrate AI-assisted workflows in architecture sessions, code reviews, and debugging.

- Build a culture where every engineer is proficient in at least one AI coding tool and actively improves their craft with it.

- Create guidelines for when to trust AI output and when to challenge it code quality gates, testing requirements, security review for AI-generated code.

- Track AI adoption metrics across the team time saved, defect rates, deployment frequency, developer satisfaction.

- Run regular AI tool evaluation cycles to ensure 301io is always using the best available tooling.

- Facilitate knowledge sharing AI prompt libraries, internal wikis, lunch-and-learn sessions on new AI capabilities.

AI-Assisted Development Standards:

- Establish AI-assisted coding standards for the full SDLC planning, design, implementation, testing, debugging, and documentation.

- Define best practices for using Claude Code for agentic tasks architecture exploration, large-scale refactors, test generation, and debugging complex systems.

- Set standards for GitHub Copilot / Gemini / Cursor usage in daily development inline completions, code explanation, review assistance.

- Create guidelines for AI-assisted debugging leveraging AI to trace root causes, generate hypotheses, and validate fixes faster.

- Establish architecture documentation practices that use AI to generate and maintain ADRs, system diagrams, and technical specs.

- Build AI-augmented code review workflows AI pre-checks before human review to catch style, security, and logic issues.

- Ensure AI tooling integrates cleanly into CI/CD pipelines AI-generated test suites, automated documentation, and quality checks.

Strategic Leadership & CTO Partnership:

- Partner closely with the CTO to translate company vision into engineering roadmaps and delivery plans.

- Represent engineering in cross-functional forums with Product, Design, Sales, and Executive leadership.

- Drive the engineering OKR process goal-setting, tracking, retrospectives, and course corrections.

- Identify and surface organisational, technical, and delivery risks proactively with proposed mitigations.

- Provide regular, transparent reporting to the CTO on team health, delivery progress, and technical debt.

- Contribute to company-level strategic planning, ensuring engineering capacity and capability inform product decisions.

People Leadership & Organisational Development:

- Lead, mentor, and inspire a multi-disciplinary team of frontend, backend, DevOps, and QA engineers.

- Own the full talent lifecycle hiring, onboarding, performance management, promotions, and exits.

- Establish clear career ladders, growth frameworks, and personal development plans for every engineer.

- Build a culture of psychological safety, continuous learning, and high accountability.

- Identify and develop future leads and senior engineers within the team.

- Partner with HR and the CTO to scale headcount in line with business needs.

- Include AI proficiency as a core competency in hiring rubrics and performance frameworks.

Solution Architecture & Technical Direction:

- Own technical architecture across all products and platforms frontend, backend, data, and infrastructure layers.

- Lead architectural decision-making author and review ADRs for all significant changes.

- Design scalable, resilient, and secure systems that support the companys 2-5 year growth trajectory.

- Evaluate and introduce new technologies, frameworks, and tools in a deliberate, risk-managed way.

- Conduct architecture reviews for new features and products before development begins.

- Define and enforce technical standards for API design, data modelling, system integrations, and security.

- Provide hands-on guidance during complex technical problem-solving and incident resolution.

Frontend Engineering Oversight:

- Set the vision and standards for frontend engineering across all 301io products.

- Drive adoption of React best practices component architecture, state management, performance optimisation.

- Oversee frontend framework decisions Next.js, Vite, Remix, or equivalent.

- Ensure high-quality, accessible, and performant UIs through strong code review and design-system governance.

- Champion AI-assisted frontend development AI-generated components, Storybook automation, accessibility checks.

Backend Engineering Oversight:

- Define backend architecture standards across Node.js services, APIs, and microservices.

- Oversee API design REST, GraphQL, gRPC consistency, versioning, and documentation.

- Drive adoption of modern backend patterns event-driven architecture, CQRS, domain-driven design.

- Govern database design choices including migration strategies and performance tuning.

- Champion AI-assisted backend development AI-generated tests, schema migrations, boilerplate elimination.

DevOps & Infrastructure Oversight:

- Partner with the DevOps Lead to align infrastructure strategy with product and engineering needs.

- Hold DevOps accountable for CI/CD maturity, platform reliability, and deployment velocity.

- Champion AI in DevOps workflows AI-assisted incident triage, runbook generation, log analysis.

- Represent engineering in cloud cost, capacity planning, and vendor management decisions.

QA & Engineering Quality Oversight:

- Set the quality bar across the organisation and enforce a consistent definition of done.

- Partner with QA leadership to build test strategies covering unit, integration, E2E, performance, and regression.

- Champion AI-assisted testing AI-generated test cases, visual regression automation, intelligent test prioritisation.

- Drive quality ownership within engineering every engineer is responsible for quality, not just QA.

Delivery, Process & Agile Execution:

- Own the engineering delivery process end-to-end sprint planning, backlog grooming, release management.

- Maintain and improve DORA metrics cycle time, deployment frequency, change failure rate, MTTR.

- Protect engineering capacity from scope creep, interruptions, and poorly defined requirements.

- Drive continuous improvement through blameless post-mortems and regular retrospectives.

- Establish and maintain clear SDLC documentation runbooks, specs, decision logs, and onboarding 8+ years of total software engineering experience, with at least 3 years in a senior engineering leadership role.

- Proven experience managing multi-disciplinary engineering teams of 10+ engineers.

- Hands-on experience using AI coding tools (Claude Code, Copilot, Gemini, Cursor, or equivalent) in a professional engineering context.

- Demonstrated track record of introducing AI-first practices into an engineering team or organisation.

- Track record of partnering with C-suite leadership to align engineering with business strategy.

- Background as a hands-on full-stack engineer before moving into leadership.

AI-First Skills & Mindset:

- Deep, practical experience with AI coding tools not just awareness, but daily use and best-practice mastery.

- Ability to teach and coach others on effective AI-assisted development prompting, context setting, output validation.

- Understanding of the risks and failure modes of AI-generated code hallucinations, security gaps, architectural drift.

- Experience integrating AI tools into CI/CD pipelines and code review workflows.

- Familiarity with LLM capabilities relevant to engineering code generation, test writing, documentation, debugging, refactoring.

- Genuine passion for the frontier of AI tooling and the ability to evaluate new tools quickly and critically.

Technical Skills Frontend:

- React (advanced), Next.js / Remix / Vite, TypeScript (expert-level), Component architecture & design systems, Web performance optimisation, State management: Redux, Zustand, Jotai, Testing: Jest, React Testing Library, Playwright, Accessibility (WCAG) standards, CSS architecture: Tailwind, CSS Modules, REST / GraphQL API consumption.

Technical Skills Backend:

- Node.js (advanced), Express, Fastify, NestJS or equivalent, REST API & GraphQL design, SQL: PostgreSQL, MySQL, NoSQL: MongoDB, Redis, DynamoDB, Microservices & event-driven architecture, Authentication: OAuth 2.0, JWT, SSO, Message queues: Kafka, RabbitMQ, SQS, API gateway and BFF patterns, Serverless architecture patterns.

Technical Skills Architecture & Breadth:

- Strong grasp of distributed systems design CAP theorem, consistency models, fault tolerance, Cloud architecture fluency AWS, GCP, or Azure services, patterns, and cost trade-offs, System design proficiency load balancing, caching strategies, CDN, database sharding, Security architecture zero-trust, encryption at rest/in transit, secrets management, IAM, Understanding of AI/ML integration patterns for AI-augmented product features, Sufficient DevOps fluency to partner effectively with the DevOps Lead.

Leadership & Soft Skills:

- Exceptional communicator equally effective with engineers, PMs, executives, and external stakeholders.

- Servant-leader mindset you get results through your team, not despite them.

- High emotional intelligence to navigate conflict, ambiguity, and organisational change.

- Data-driven decision maker comfortable defending architectural and organisational trade-offs.

- Bias for action and ownership you close loops and do not let things fall through the cracks.

- Strategic thinker who can zoom out to business context and zoom in to implementation Experience in a high-growth startup or scale-up environment.

- Background in platform engineering and developer experience (DX) initiatives.

- Exposure to AI product development and LLM-based feature integration.

- Prior experience setting AI adoption metrics and tooling evaluation frameworks.

AI Tools We Expect You to Know and Champion:

301io provides every engineer with access to leading AI development tools. As Head of Engineering, you are expected to be proficient across this landscape and to raise the bar for how these tools are used.

- Claude Code: Agentic coding, architecture Q&A, complex refactors.

- GitHub Copilot: Inline completions, test generation, PR summaries.

- Gemini / Vertex AI: Code review, doc generation, multi-modal tasks.

- Cursor / Windsurf: AI-native IDE with codebase-aware completions.

Our standard for AI-assisted engineering:

We do not accept AI as a shortcut that bypasses quality. We expect AI-first engineers to write better, more tested, better-documented code faster. AI removes toil; it does not remove ownership. Every engineer at 301io is accountable for the code they ship, regardless of how it was generated.

301io Technology Landscape:

You will lead teams working across this stack. You need not be expert in every tool, but you must make sound decisions across the full landscape and identify where AI tooling creates the highest React + TypeScript, Next.js / Vite, Tailwind CSS, Playwright / Cypress, Figma to code Node.js / NestJS, PostgreSQL + Redis, GraphQL + REST APIs, Kafka / SQS, Serverless (Lambda).

Infrastructure & AI:

- AWS (primary cloud), Kubernetes + Docker, GitHub Actions CI/CD, OpenAI / Anthropic APIs, Prometheus + Grafana.

(ref:hirist.tech)