Engineering · Technology Leadership
Head of Engineering
It is a high-trust, high-ownership role with direct influence on product direction.
Experience
10–15 years
Location
Bengaluru
Level
Experienced
About the Role
NewStreet is building an AI-native enterprise platform where intelligent agents generate application configurations from natural language, and deterministic execution engines run them in production — letting organisations in regulated industries launch workflows in days rather than months.
You own the technical shape of the platform — architecture, the build-once boundary, non-functional requirements, and the deployment and operations practice that carries it into production.
It is a high-trust, high-ownership role with direct influence on product direction. You work through the function leads rather than a direct team, and you are measured on whether standards actually land in production code.
Key Responsibilities
Architecture & Technical Strategy
Lead system architecture decisions
Challenge assumptions, propose alternatives, evaluate trade-offs, and drive to closure rather than leaving options open.
Own Architecture Decision Records
Establish and enforce ADRs that govern critical platform choices, so decisions outlive the people who made them.
Hold architectural consistency
Multi-tenant isolation, configuration-driven execution, event-driven communication and API contract discipline across every function.
Draw the build-once line
Decide what becomes product capability versus per-client configuration — and hold that line when a deal pushes against it.
Own the non-functionals
Performance, availability, cost per transaction and security posture: defined, measured and defended.
Balance quality against speed
Prioritise technical debt strategically without stalling product momentum.
DevOps, Deployment & Operations
Own the engineering side of DevOps
CI/CD pipeline design, release management, environment governance and rollback strategy — make deployment boring and repeatable.
Set the infrastructure-as-code standard
Containerised deployment, Kubernetes, Terraform, and the same pipeline shape for cloud and on-premise client estates.
Champion observability
Structured logging, distributed tracing, metrics and alerting designed in at build time, not retrofitted after an incident.
Design for production reliability
Failure modes, degradation behaviour, capacity headroom and incident-response readiness as architectural concerns.
Drive SLA adherence
Operational excellence for all client-facing systems, with the architecture to support it.
AI, GenAI & Product Strategy
Shape the AI architecture
How agents, LLMs and intelligent automation are applied to real enterprise problems in regulated industries.
Own the AI / deterministic boundary
Identify where intelligent automation adds value and where predictability is non-negotiable.
Evaluate the landscape
Commercial models, open-weight alternatives, multi-agent orchestration patterns — and translate them into engineering decisions.
Bring working AI fluency
RAG pipelines, prompt engineering, LLM evaluation, guardrails and agent-based architectures.
Leadership & Client Engagement
Run the design-review gate
A review every function lead uses before significant work starts, fast enough that nobody routes around it.
Take architecture decisions off the CTO
Become the escalation point for technical trade-offs across the four functions you own — Platform Engineering, AI / ML, Information Security and DevOps.
Mediate and mentor
Resolve technical disagreements, raise the bar on design documents and code review, and grow the leads beneath you.
Represent engineering to clients
Solution architecture walkthroughs, feasibility discussions and technical credibility with enterprise banking stakeholders.
Drive hiring
Assess for technical depth and problem-solving as the organisation scales past fifty.
What You Bring
- 10–15 years in software engineering with at least 3–4 in a leadership or architecture-owning capacity. BE / BTech / MCA or equivalent, Master's preferred.
- Product company experience is essential — you have built, shipped and iterated on a software product, not solely services or staff-augmentation delivery.
- Strong system-design fundamentals: distributed platforms, trade-off evaluation, sound decisions under ambiguity.
- Hands-on with a modern backend stack — Python / FastAPI strongly preferred; Java / Spring Boot, Go or Node.js acceptable. You still read and review code.
- Solid working knowledge of PostgreSQL, caching (Redis) and message brokers (Kafka or equivalent).
- Cloud-native infrastructure and DevOps depth — Docker, Kubernetes, Terraform or equivalent IaC, CI/CD ownership, and at least one major cloud (AWS preferred). Credible on-premise deployment experience: several clients will never run in a public cloud.
- Demonstrable Generative AI understanding — practical, not conversational: RAG, prompt engineering, function calling, agent patterns, evaluation and guardrails.
- Confident communicator, comfortable presenting to CXO-level stakeholders and holding the room in a technical discussion.
- A track record of standards being adopted by teams that do not report to you. Influence without authority is the core of this job.
What Would Be Great to Have
- Domain experience in fintech, banking, lending or insurance.
- Multi-tenant SaaS architecture — tenant isolation strategies, configuration management, data governance at scale.
- Configuration-driven or low-code / no-code platform architecture.
- ISO 27001, ISO 42001, SOC 2, DPDPA or RBI compliance frameworks from the engineering side.
- LLM orchestration frameworks — LangChain, LangGraph, CrewAI or custom implementations.
- Observability tooling built rather than bought; SRE practice established from scratch.
- Track record of scaling an engineering team through a growth phase (15 to 30+ engineers).
Why Join Us
The platform is at an inflection point — the architecture is defined, the specifications are complete, and the team is building. This is a rare chance to own the technical shape of an AI-native enterprise product from its formative stage, with direct influence on how AI reshapes regulated industries.
What We Offer
- A seat at the technology leadership table, with direct influence on product direction and engineering culture.
- Ownership of architecture and the DevOps practice for a platform serving regulated financial institutions.
- Hands-on exposure to multi-agent systems, LLM orchestration and intelligent automation applied to real problems.
- A lean, high-calibre team where individual decisions carry outsized impact.
- Competitive compensation aligned with experience and market benchmarks.
Sound like you?
Send your CV to careers@newstreettech.com. The subject line is filled in with the role code (NS-ARC-001) for you.
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