Engineering Lead - workflow Orchestration at Tech AI startup in Bangalore · Remote only · 7 - 10 years · ₹15L - ₹25L / yr · Remote only · Posted 21 Nov 2025

Engineering Lead - workflow Orchestration
at Tech AI startup in Bangalore
We are seeking a seasoned Engineering Lead with deep expertise in workflow orchestration systems, stateful execution engines, and distributed task runtimes. You will architect the next generation of our DAG-based runtime, develop the infrastructure for agentic workflow composition, and drive execution excellence across engineering. This role combines hands-on systems design with technical leadership and team mentorship.
Key Responsibilities
1. Architect & Build the Swarm Runtime
- Design and implement a DAG-based orchestration engine using Temporal, Argo Workflows, or equivalent event-driven runtimes.
- Build a scalable primitive registry for tasks, operators, guards, and computational nodes.
- Architect a robust scheduler capable of handling event triggers, retries, backoffs, and distributed coordination.
2. Develop the Workflow Composition Layer
- Define and build a YAML/JSON-based DSL for describing agentic workflows, dependencies, and execution semantics.
- Create a schema-driven rules engine ensuring validations, model calls, parallelism, conditional branching, and approval gates are seamlessly integrated.
3. Orchestration Logic & Runtime Intelligence
- Implement orchestration logic that coordinates:
- Validation layers
- Model calls (LLMs, embedding engines, external APIs)
- Human-in-the-loop approval gates
- Stateful transitions and checkpointing
- Ensure deterministic execution, traceability, and safe rollback mechanisms.
4. Workflow Certification & Automated Testing
- Define certification standards for every workflow type, including:
- Functional correctness
- Latency and concurrency thresholds
- Error-handling expectations
- Observability and trace coverage
- Build automated regression test suites validating workflow integrity before deployment.
5. Engineering Leadership & Delivery
- Lead, mentor, and grow a team of backend and systems engineers.
- Drive sprint planning, reviews, engineering discipline, and roadmap execution.
- Own runtime delivery deadlines, cross-team coordination, and release quality.
6. Observability, Reliability & Production Excellence
- Instrument the runtime with observability hooks: metrics, tracing, structured logs, and execution heatmaps.
- Build robust retry logic, distributed locks, idempotency guards, and failover strategies.
- Improve runtime stability, throughput, and scale characteristics.
Requirements
Must-Have
- 8+ years of backend engineering experience building high-scale systems.
- 3+ years leading teams focused on workflows, automation, orchestration, or distributed runtimes.
- Deep understanding of:
- Stateful orchestration engines (Temporal, Step Functions, Argo, Airflow)
- Message queues, pub/sub systems, and event-driven patterns
- Retry logic, compensating transactions, and idempotent operations
- Distributed tracing, observability pipelines, and health checks
- Strong background in concurrent programming, async task management, and execution models.
- Hands-on experience with at least one systems language or backend stack (Python, Go, Rust, Node).
Nice-to-Have
- Experience building workflow DSLs or schema-driven interpreters.
- Familiarity with LLM pipelines, agentic runtimes, or AI-driven workflow automation.
- Knowledge of Kubernetes-based runtime environments and workflow controllers.
- Experience with pluggable architecture design, sandboxing, or execution policies.
What This Role Offers
- Ownership of the core execution engine powering Perceive Now’s intelligent automation platform.
- A high-impact leadership position shaping architectural strategy and engineering culture.
- The opportunity to solve cutting-edge problems at the intersection of orchestration, distributed systems, and AI.

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About the Role
We are hiring Staff / Principal Engineers to take full, hands-on ownership of Blitzy's most critical production-grade systems and to deliver high-leverage features that materially improve customer outcomes and engineering velocity. This is the most senior individual contributor role at the company today.
This is not a Senior-plus role, an architecture-only role, or a promotion-track role. We are looking for someone who has already operated at Principal / Staff+ scope in a highly technical environment and expects to spend their time writing, reviewing, and shipping production code.
This role is 100% hands-on. Leverage comes from system ownership, execution quality, and durable technical decisions — not people management or process.
Responsibilities
- Own mission-critical production systems end-to-end, ensuring correctness, scalability, performance, reliability, and operational excellence.
- Design, build, and ship high-impact backend systems and features that improve product reliability, performance, and customer value.
- Architect scalable services and cloud infrastructure using technologies such as Python, REST, gRPC, Kubernetes, and Terraform.
- Identify and resolve complex technical bottlenecks that limit engineering quality, system performance, or organizational velocity.
- Build and operate LLM-powered systems and validation loops that evaluate correctness, consistency, durability, and production performance.
- Design and evolve data architectures incorporating relational, NoSQL, graph, and vector databases to support complex enterprise applications and semantic retrieval.
- Modernize and improve complex enterprise systems while balancing reliability, maintainability, scalability, and delivery speed.
- Set and uphold engineering quality standards through hands-on technical leadership, sound technical judgment, and ownership of long-term technical decisions.
Qualifications
- Direct experience with Python as a primary programming language, backend frameworks, and microservices architectures.
- Expertise in REST and gRPC, with proficiency in Node.js and JavaScript.
- Proficiency in GCP, along with experience using at least one additional cloud platform such as AWS or Azure.
- Advanced knowledge of Kubernetes and Terraform in production environments.
- Experience operating highly available production systems, including monitoring, scalability, reliability, performance optimization, and operational tooling.
- Strong knowledge of SQL and NoSQL databases, including PostgreSQL, MySQL, MongoDB, Cassandra, or DynamoDB.
- Familiarity with graph databases such as Neo4j and vector databases or embedding infrastructure for semantic search and retrieval.
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- Ability to contribute across the full stack, with a strong understanding of frontend architecture and the ability to debug, design, and ship across frontend, backend, infrastructure, and AI systems.
- Understanding of large-scale enterprise software systems, including architecture, integration, deployment, modernization, and long-term maintainability.
- Proven track record of operating at Staff+, Principal Engineer, or equivalent level, independently driving complex technical initiatives and delivering high-impact outcomes with minimal supervision.
Blitzy is a Cambridge, MA based AI software development platform on a mission to revolutionize the software development life cycle by autonomously building custom software to unlock the next industrial revolution. We're transforming how enterprises build software, turning enterprise requirements into enterprise grade code with an agentic software development platform that can autonomously execute 80% of the quantum of software development work. We're backed by multiple tier 1 investors, and have proven success as founders of previous start-ups.
Our Culture
Who we are:
Led by two pioneering co-founders we are one of the fastest growing companies in the U.S., creating our own category of enterprise autonomous software development. We automate thousands of hours of software development for our customers, which includes strong representation within the Fortune 500.
How we work:
- We move Blitzy Fast: Time is both our company’s and our clients’ most precious asset. We move quickly and decisively to innovate internally and deliver exceptional software externally.
- Championship Mindset: We operate like a professional sports team. We win as a team by holding ourselves and each other to high standards, collaborating in-person, and remaining focused on the mission.
- Passion for Invention: We’re pushing the frontier of what’s possible, requiring constant innovation and iteration.
- We Work for the Customer: We focus on delivering outsized value to the customers we work with and expanding those relationships into deep, meaningful partnerships.
- We believe in being ‘everyday athletes’: taking care of ourselves so we can bring our best minds to work. We promote great sleep, movement, and restorative activities for
Blitzy is an equal opportunity employer committed to building a diverse and inclusive team. We believe different perspectives make us stronger.
About the Company
As the world moves toward AI-native applications, one element matters more than anything: data.
We are building a platform that helps organizations unlock the value hidden within customer feedback. By centralizing data from multiple sources—including CRM platforms, support systems, collaboration tools, surveys, community forums, and customer conversations—into a unified intelligence layer, we enable teams to understand customer needs and make better product decisions.
Built on top of this foundation is an AI-powered platform that allows teams to query, monitor, and act on customer intelligence directly within their workflows. Our customers include some of the fastest-growing product-led technology companies as well as large global enterprises.
Backed by leading global venture capital firms, our engineering culture is AI-native from the ground up. Agents, LLMs, and applied machine learning are not side projects—they are central to how we build products. We operate at the cutting edge of agentic systems and continuously push the boundaries of what modern AI applications can achieve.
What You Will Do
- Convert product direction into phased technical plans, including estimates, milestones, dependencies, and risk assessments.
- Make thoughtful trade-offs across correctness, latency, user experience, AI/model behavior, reliability, cost, and delivery speed.
- Define clear ownership boundaries across frontend applications, BFF layers, backend services, agent workflows, ML platforms, and data contracts.
- Review ERDs, PRDs, design documents, and implementation plans to identify gaps before they become execution challenges.
- Drive planning and execution for complex initiatives while empowering area leads and senior engineers to maintain ownership.
- Partner closely with Product, Design, Engineering, and GTM teams to turn ambiguous problem statements into executable solutions.
- Influence technical direction through strong engineering judgment, architectural leadership, and hands-on involvement.
- Mentor senior engineers and contribute to engineering excellence through reviews, incident analysis, and proactive risk management.
What It Takes
- 5+ years of experience as a Senior Engineer, Technical Lead, or equivalent role.
- Demonstrated experience owning architecture and execution for large-scale product or platform initiatives spanning multiple teams.
- Strong foundation in distributed systems and modern software architecture.
- Exposure to agentic AI systems, machine learning engineering, MLOps platforms, and frontend/BFF architectures.
- Ability to own end-to-end product and technical problems rather than specializing exclusively in a single layer of the stack.
- Proven track record of converting ambiguity into actionable engineering plans.
- Excellent written communication skills, including design documentation, architectural reviews, trade-off analyses, and RCA documentation.
- Ability to challenge requirements constructively and collaborate effectively across Product, Design, Engineering, and GTM functions.
- High ownership mindset, attention to detail, and a low-ego, collaborative approach.
About the Role
We are seeking a hands-on Tech Lead to design, build, and integrate AI-driven systems that automate and enhance real-world business workflows. This is a high-impact role for someone who enjoys full-stack ownership — from backend AI architecture to frontend user experiences — and can align engineering decisions with measurable product outcomes.
You will begin as a strong individual contributor, independently architecting and deploying AI-powered solutions. As the product portfolio scales, you will lead a distributed team across India and Australia, acting as a System Integrator to align engineering, data, and AI contributions into cohesive production systems.
Example Project
Design and deploy a multi-agent AI system to automate critical stages of a company’s sales cycle, including:
- Generating client proposals using historical SharePoint data and CRM insights
- Summarizing meeting transcripts
- Drafting follow-up communications
- Feeding structured insights into dashboards and workflow tools
The solution will combine RAG pipelines, LLM reasoning, and React-based interfaces to deliver measurable productivity gains.
Key Responsibilities
- Architect and implement AI workflows using LLMs, vector databases, and automation frameworks
- Act as a System Integrator, coordinating deliverables across distributed engineering and AI teams
- Develop frontend interfaces using React/JavaScript to enable seamless human-AI collaboration
- Design APIs and microservices integrating AI systems with enterprise platforms (SharePoint, Teams, Databricks, Azure)
- Drive architecture decisions balancing scalability, performance, and security
- Collaborate with product managers, clients, and data teams to translate business use cases into production-ready systems
- Mentor junior engineers and evolve into a broader leadership role as the team grows
Ideal Candidate Profile
Experience Requirements
- 5+ years in full-stack development (Python backend + React/JavaScript frontend)
- Strong experience in API and microservice integration
- 2+ years leading technical teams and coordinating distributed engineering efforts
- 1+ year of hands-on AI project experience (LLMs, Transformers, LangChain, OpenAI/Azure AI frameworks)
- Prior experience in B2B SaaS environments, particularly in AI, automation, or enterprise productivity solutions
Technical Expertise
- Designing and implementing AI workflows including RAG pipelines, vector databases, and prompt orchestration
- Ensuring backend and AI systems are scalable, reliable, observable, and secure
- Familiarity with enterprise integrations (SharePoint, Teams, Databricks, Azure)
- Experience building production-grade AI systems within enterprise SaaS ecosystems
Role & Responsibilities
Responsibilities
• Business: Immerse in operations until you think like an insider.
Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.
• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.
• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.
• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.
• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.
• Scale: Design complex multi-component systems end-to-end, evaluate architectural options for large initiatives across teams, guide technical decisions for your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.
• Documentation: Define documentation standards across teams in your area, create documentation systems and templates, train engineers on spec-driven development, and ensure documentation quality across projects. Lead pattern generalization initiatives, defining criteria for when to generalize versus keep custom.
• Reliability: Define reliability standards across teams in your area, drive post-incident improvements systematically, design capacity planning processes, andmentor engineers on SRE practices.
Ideal Candidate
- Strong Staff Software Engineer / FDE profile (full-stack + production GenAI, multi-team technical leadership)
- Mandatory (Experience 1) – Must have 7+ years of relevant professional software engineering experience, with demonstrated full-stack delivery across backend and frontend.
- Mandatory (Experience 2) – Must have deep production experience with Python AND JavaScript/TypeScript, working comfortably across the full stack.
- Mandatory (Experience 3) – Must have 2+ years of experience in generative AI applications developement — LLM integrations, vector databases, RAG systems, and evaluation pipelines
- Mandatory (Experience 4) – Must have strong experience with modern frontend frameworks (Next.js / React) and backend API development.
- Mandatory (Experience 5) – Must have extensive experience with cloud platforms (AWS preferred; Azure/GCP valued), including infrastructure-as-code (CloudFormation / Terraform).
- Mandatory (Experience 6) – Must have working knowledge of multiple database paradigms — relational (PostgreSQL), document, and key-value (Redis) — with ability to select the right storage per problem.
- Mandatory (Experience 7) – Must have strong experience with CI/CD pipelines (e.g. GitHub Actions), containerization, and production deployment strategies.
- Mandatory (Experience 8) – Must have demonstrable fluency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on them
- Preferred (Experience) – Advanced RAG techniques — hybrid search, reranking, query expansion — and establishing RAG standards across teams







