Engineering Lead - workflow Orchestration

Supercharge Your Career as a Principal Lead Developer at Technoidentity!

At Technoidentity, we're a Data & AI product engineering company with over 15 years of expertise in building durable digital products, intelligent enterprise solutions, and scalable Data & AI platforms. As we continue expanding globally, it's the perfect time to join our team of tech innovators and make a lasting impact.

What’s in it for You?

Technoidentity is building a high-impact Temporal Capability Center to design, deliver, and scale resilient workflow-orchestration solutions for enterprise customers. We are seeking a hands-on, technically strong Principal Lead Developer who combines deep software-engineering expertise with solution-architecture leadership, distributed-systems knowledge, and an ownership mindset.

This role is suited to a resourceful engineer who can independently take multi-faceted business and technical requirements from discovery through design, implementation, rollout, and operational improvement. You will work directly with overseas clients, shape architecture decisions, lead multiple technical workstreams, and mentor junior developers while remaining actively involved in code, design reviews, and delivery.

The ideal candidate has strong practical experience in Python, Java, and/or TypeScript, has experience with Cloud Platforms, understands modern AI-assisted engineering practices. Experience with distributed workflow solutions using orchestration platforms such as Temporal, Cadence, Camunda, or similar technologies will be preferred, but is not a requirement.

Requirements

What Will You Be Doing?

• Lead the end-to-end technical delivery of workflow-orchestration and distributed-systems solutions for enterprise clients.
• Design robust, scalable, secure, and observable architectures using durable execution, asynchronous messaging, APIs, event-driven patterns, and cloud-native components.
• Build production-grade services and workflow implementations using Python, Java, and/or TypeScript.
• Design and implement long-running business processes using orchestration frameworks such as Temporal, Cadence, Camunda, or equivalent platforms.
• Apply distributed-systems principles to address reliability, idempotency, retries, timeouts, compensating transactions, eventual consistency, failure recovery, and data consistency.
• Design and implement Saga patterns, including orchestration-based and choreography-based approaches, for multi-service business transactions.
• Lead architecture discovery sessions, technical workshops, solution presentations, and design reviews with overseas clients and internal stakeholders.
• Translate business requirements into clear solution architectures, implementation plans, technical specifications, estimates, and delivery milestones.
• Drive multiple concurrent technical streams, identify dependencies and risks early, and maintain delivery quality under changing priorities.
• Establish engineering standards for workflow design, API contracts, error handling, versioning, testing, deployment, observability, and operational readiness.
• Use AI-assisted SDLC practices responsibly to improve developer productivity, code quality, test coverage, documentation, and delivery velocity.
• Design and contribute to agentic orchestration solutions, including coordination of AI agents, tool/API integrations, workflow state management, guardrails, human-in-the-loop controls, and evaluation approaches where relevant.
• Perform hands-on development of critical components, prototypes, integrations, and reference implementations.
• Conduct code reviews and architectural reviews, ensuring solutions are maintainable, performant, secure, and aligned with engineering best practices.
• Mentor and guide junior developers; support technical growth through pairing, reviews, reusable patterns, technical sessions, and constructive feedback.
• Collaborate with delivery, product, platform, QA, DevOps, security, and client teams to ensure successful implementation and production adoption.
• Contribute reusable assets, accelerators, templates, documentation, and best practices to the Temporal Capability Center.

Benefits

What Makes You the Perfect Fit?

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical discipline, with 6+ years of relevant work experience.
• Significant professional software-development experience, including experience leading technical delivery and mentoring engineering teams.
• Strong hands-on proficiency in at least one of the following languages:

o  Python

o  Java

o  TypeScript

• Demonstrated experience designing and building distributed, scalable, highly available, or event-driven systems.
• Strong understanding of microservices architecture, REST and/or asynchronous APIs, message-driven systems, and integration patterns.
• Practical expertise with distributed-systems concerns, including:

o  Idempotency and duplicate-message handling

o  Retries, backoff, timeouts, and circuit-breaking strategies

o  Failure handling and recovery

o  Eventual consistency and data synchronization

o  State management for long-running processes

o  Observability, logging, metrics, tracing, and operational debugging

• Strong understanding and practical application of the Saga pattern and compensating-transaction design.
• Experience designing solution architectures and communicating technical trade-offs to both engineering and business stakeholders.
• Ability to lead junior developers through technical direction, task decomposition, code review, and mentorship.
• Strong written and verbal communication skills in English.
• High ownership, self-motivation, adaptability, and the ability to make sound decisions in ambiguous and fast-moving environments.

Preferred Qualifications

• Production experience with Temporal, Cadence, Camunda, AWS Step Functions, Azure Durable Functions, Netflix Conductor, Apache Airflow, or comparable orchestration technologies..
• Experience migrating from legacy schedulers, BPM platforms, or synchronous microservice flows to durable workflow orchestration.
• Experience building agentic or AI-enabled applications using LLMs, tool calling, agent frameworks, retrieval-augmented generation, MCP, guardrails, or evaluation frameworks.
• Practical use of AI coding assistants and AI-aided SDLC workflows for planning, implementation, testing, code review, documentation, and troubleshooting.
• Cloud-native development experience on AWS, Azure, Google Cloud Platform, or a hybrid-cloud environment.
• Experience with Kubernetes, Docker, CI/CD pipelines, Infrastructure as Code, and container-based deployments.
• Experience with event-streaming and messaging platforms such as Kafka, RabbitMQ, cloud queues, or pub/sub systems.
• Experience with relational and NoSQL databases, data-modeling strategies, and transactional/outbox patterns.
• Experience with API gateways, security controls, OAuth/OIDC, secrets management, and secure service-to-service communication.
• Familiarity with domain-driven design, event sourcing, CQRS, and enterprise integration patterns.
• Experience in technical consulting, pre-sales support, solution accelerators, or client-facing technical leadership.

Leadership Expectations

As a Principal Lead Developer, you will be expected to:

• Act as a trusted technical advisor to clients and internal delivery teams.
• Balance architecture leadership with hands-on engineering execution.
• Proactively identify problems, propose practical solutions, and drive them to completion without waiting for detailed direction.
• Manage and prioritize several workstreams while communicating progress, risks, decisions, and dependencies clearly.
• Raise engineering quality through reusable standards, design patterns, code reviews, and mentoring.
• Build confidence with clients through technical depth, clarity, responsiveness, and reliable delivery.
• Foster a collaborative, accountable, learning-oriented engineering culture within the Temporal Capability Center.

Success Measures

Success in this role will be measured by:

• Delivery of reliable, scalable, and maintainable orchestration solutions that solve real client problems.
• Quality of solution architecture, code, technical documentation, and operational readiness.
• Effective application of workflow-orchestration and Saga patterns to complex distributed business processes.
• Ability to independently lead client-facing technical discussions and turn them into executable delivery plans.
• Delivery predictability across multiple concurrent technical initiatives.
• Measurable improvement in engineering productivity and quality through AI-assisted SDLC practices.
• Growth, engagement, and technical effectiveness of junior developers under your guidance.
• Contribution of reusable Temporal Capability Center assets, reference architectures, and best practices.

Why Join Technoidentity’s Temporal Capability Center?

• Work on complex, high-value enterprise workflow and distributed-systems challenges.
• Help shape a specialized capability center focused on durable execution, orchestration, AI-enabled delivery, and modern architecture.
• Collaborate with overseas clients and multidisciplinary global teams.
• Influence technical standards, reusable accelerators, and the future direction of orchestration solutions at Technoidentity.
• Take on a role with meaningful architecture ownership, technical leadership, and hands-on engineering impact.

Required Experience: 10–15 years (with at least 3–5 years in leadership roles)

● 10–15 years of overall experience in backend engineering, with strong exposure to

Python and/or Golang.

● 3–5 years of experience managing engineering teams.

● Proven experience delivering large-scale, distributed systems in production

environments.

● Strong understanding of microservices, cloud-native architecture, and DevOps

practices.

● Hands-on background in backend engineering (able to guide teams technically, even

if not coding daily).

● Familiarity with CI/CD pipelines, observability, and performance optimization.

● Experience in financial services or high-transaction domains is a plus.

● Experience leading teams that have utilized AI-driven development practices (e.g.,

agentic coding, LLM integration) to improve productivity and innovation is a

significant advantage.

Skills

● Excellent leadership and people management abilities.

● Strong communication and stakeholder management skills.

● Ability to balance technical depth with business priorities.

● Problem-solving mindset with a focus on delivery and impact.

● Passion for building engineering culture and improving developer experience.

Why this role exists 

Most systems work at a low scale. 

Very few survive real production load, complex workflows, and enterprise edge cases. 

We are building a platform that must: 

1. Scale from 500K → 20M+ interactions/month 
2. Handle complex insurance workflows reliably 
3. Become easier to deploy as it grows, not harder 
4.  
5. This role exists to build the backend foundation that makes this possible. 

What you’ll do 

You will not just write services. 

You will design and own core platform systems. 

1. Scale the platform without breaking architecture 

1. Scale from 50K → 4M+ interactions/month 
2. Ensure: 
3. High availability 
4. Low latency 
5. Fault tolerance 
6. Avoid large rewrites — build systems that evolve cleanly 

2. Build the workflow automation (WA) engine 

1. Design a flexible system with: 
2. States 
3. Stages 
4. Cohorts 
5. Dynamic workflows 
6. Ensure workflows: 
7. Handle edge cases reliably 
8. Can be configured easily 
9. Move from: 
10. Hardcoded flows → configurable execution engine 

3. Build the insurance-specific data layer 

1. Design data models for: 
2. Policy states 
3. Claim workflows 
4. Consent tracking 
5. Ensure the system works across: 
6. Multiple insurers 
7. Multiple use cases 
8. Build a platform-first data layer, not use-case-specific hacks 

4. Make deployment and setup simple 

1. Ensure workflows and data models are: 
2. Easy to configure 
3. Easy to launch 
4. Reduce friction for: 
5. Product teams 
6. Deployment teams 

5. Create a compounding data advantage 

1. Build a data layer that: 
2. Improves with every deployment 
3. Captures structured signals 
4. Ensure data becomes a long-term edge, not just storage 

6. Own production reliability 

1. Participate in on-call rotation across 3 engineers 
2. Ensure: 
3. Incidents are handled quickly 
4. Root causes are fixed permanently 
5. Build systems where reliability is shared, not individual 

What success looks like 

1. Platform scales to 2M+ interactions/month smoothly 
2. Workflow engine supports complex, dynamic use cases 
3. Data layer enables fast deployment across accounts 
4. Edge cases are handled without constant firefighting 
5. System becomes easier to use as it grows 
6. Production issues are rare and predictable 

Who you are 

1. You have built: 
2. Scalable systems 
3. Distributed services 
4. You think in: 
5. Systems 
6. Data models 
7. Trade-offs 
8. You are comfortable owning: 
9. Architecture 
10. Production systems 

What will make you stand out 

1. Experience building: 
2. Workflow engines 
3. State machines 
4. Data-heavy platforms 
5. Strong understanding of: 
6. System design 
7. Distributed systems 
8. Failure handling 
9. Experience working in: 
10. High-scale production environments 

Why join 

1. You will build the core backend of an AI platform 
2. Your work directly impacts: 
3. Scale 
4. Reliability 
5. Product capability 
6. You will design systems that move from: 
7. Use-case specific → platform-level infrastructure 

What this role is not 

1. Not just API development 
2. Not limited to feature-level work 
3. Not disconnected from production realities 

What this role is 

1. A system architect 
2. A builder of scalable platforms 
3. A driver of long-term technical advantage 

One question to self-evaluate 

Can you design backend systems that scale, handle edge cases, and become easier to use as they grow? 

Tech Lead – Backend

Roles & Responsibilities

The company is building the operational backbone for how B2B enterprises run their business.

As a Tech Lead on the backend team, you will own the technical direction for a core domain of the platform—systems where correctness is non-negotiable, scale is unforgiving, and edge cases never stop coming. You will also mentor Senior Engineers in your pod.

This is a hands-on role: you will write code and design systems yourself day to day, pair on complex problems, review the work of engineers around you, and be the person who figures out what's actually broken before it becomes a fire.

You will report into the Engineering Manager / Head of Engineering. This is not a feature-factory role. You are here to raise the level of abstraction the team works at, not simply to ship tickets faster.

What You'll Own

• Design and build core platform services that handle complex business logic reliably at scale.
• Architect and own integrations with external enterprise systems, including their quirks, rate limits, and failure modes.
• Build APIs that enterprise engineering teams actually want to integrate with, not just ones that technically work.
• Own production debugging end to end: diagnose issues across services using logs, traces, and metrics, and make incidents boring rather than fires.
• Embed security and compliance thinking into your systems by default, not as a retrofit.
• Mentor Senior Backend Engineers in your pod: pair on hard problems, review their work, and help them grow as engineers.
• Set the architectural direction for your domain: choose frameworks, patterns, and abstractions that shape the platform for years.
• Lead design reviews and code reviews, and set the technical standard the rest of the team calibrates against.
• Hold a clear bar for quality, follow-through, and ownership across the engineers you work with, ensuring systems are healthy in production, not just merged.
• Partner with Product, Implementation, and Customer Success as the engineer who understands the system deeply enough to challenge requirements when necessary.
• Raise the technical bar for the engineers around you without slowing the team down.
• 
  

Ideal Candidate

1. Strong Tech Lead / Staff Engineer / Lead Engineer Profile

• Proven experience operating at Tech Lead, Staff Engineer, or Lead Engineer level.

1. Mandatory – Overall Experience

• Minimum 6+ years of overall Software Engineering / Development experience building production backend systems.

1. Mandatory – Tech Lead Ownership

• Proven Tech Lead ownership with experience setting technical direction, architecture, frameworks, or engineering standards used by other engineers.

1. Mandatory – Backend Development

• Strong hands-on backend development experience with deep proficiency in at least one backend programming language such as Python, Java, or Golang.

1. Mandatory – System Design & Distributed Systems

• Strong experience in system design and distributed systems, including architectural trade-offs, scalability, failure modes, reliability, and long-term maintainability.

1. Mandatory – APIs & Integrations

• Experience designing and building APIs, backend services, and external/enterprise integrations.
• Strong experience owning complex business logic and production systems.

1. Mandatory – Technical Leadership

• Formal technical leadership experience, including mentoring Senior Engineers, conducting design and code reviews, driving engineering quality, and leading technical decisions across a team.

1. Mandatory – Hands-on IC + Tech Lead

• Must be a hands-on Individual Contributor + Tech Lead, with approximately 70–80% hands-on coding/engineering involvement.
• Pure people-management profiles are not suitable.

1. Mandatory – Company Background

• Experience working in Product Companies, Startups, or B2B SaaS organizations.

1. Mandatory – Education

• CS degree or equivalent, such as B.Tech / B.E. / B.S.

1. Preferred – Technical Skills

• Experience with Kafka, NATS, RabbitMQ
• AWS
• Docker / Kubernetes
• CI/CD
• Observability and monitoring
• Security and compliance
• Multi-tenant systems
• Financial, billing, or enterprise platforms

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.
• Hands-on experience building and operating LLM-powered systems in production, including evaluation, validation, regression testing, tracing, and failure analysis.
• Working knowledge of LangSmith or comparable LLM observability and evaluation tools; familiarity with OpenAI, Anthropic, or similar model providers is a plus.
• 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 Juicelabs

Where creative engineering meets applied AI.

We build vertical, AI-native tools that unlock fresh insights and creative superpowers for clients in advertising, ecommerce, and beyond. We're a nimble team of founders and builders obsessed with using AI to solve real problems in ways that didn't exist eighteen months ago.

The Opportunity

A year ago, we would have posted this as a backend role. That role doesn't really exist any more.

Code has become nearly invisible. Agents write it, test it, and iterate on it faster than anyone could read it. What's left is the work above it: deciding what's worth building, designing systems that hold up at 10x, and building the setup that turns a clear spec into working software.

That's the job. At your level, it isn't one system. It's several workstreams, running at once.

You'll work directly with our Cofounder/CTO on products going from zero to one, with AI at the core of both what we build and how we build it. Real ownership, real scope, and an unusual amount of leverage: one engineer with good judgment and a well-tuned agent setup now ships what a small team used to.

What you'll do

• Own multiple workstreams in parallel. Two or three features of the same product moving at once, each with its own scope, edge cases, and failure modes. You decide where your attention goes this week, and nothing goes stale.
• Run a fleet, not a single agent. Design the setup that makes high-throughput work possible: how work gets broken down, specced, and run across many agents at once, so output scales without things breaking.
• Design the system. Service boundaries, data models, failure modes. Make the architectural calls before a line gets generated, and be able to explain the trade-off six months later.
• Write the spec. PRDs and technical designs are the new source code. A vague spec produces confidently wrong software, fast. Scope, edge cases, non-goals, what "done" means.
• Own it end to end. Ideation → design → build → deploy → monitor → iterate, including functional UX. Nobody hands you tickets.
• Set the workflow. Bring your harness: CLAUDE.md, AGENTS.md, subagents, custom commands, eval loops — whatever makes agents reliable rather than merely impressive. We want to steal your good ideas.

What we're looking for

• High agency. You see the gap and close it. You don't wait for direction, and you don't need to be chased for follow-through. This is the single trait we screen hardest for. And you can do it across several workstreams at once, without dropping threads.
• Real system design depth. You can reason about consistency, caching, queues, and scale — and about complexity, because you need to know when an elegant-looking solution is quietly quadratic. LeetCode ninja not required. Being able to explain why this won't blow up at 10x, very much required.
• Clear thinking, put to paper. You get the thinking straight first, then write it down so nobody has to guess: PRDs, design docs, PR comments. Writing is most of how you'll direct both humans and models, and muddy thinking on paper becomes muddy software.
• You've shipped to production. Deployed things, monitored them, been paged by them, fixed them. Docker, CI/CD, cloud infra. Our stack is mostly Python (FastAPI), Postgres, GCP/AWS — but we care more about how you think than which framework you've memorised.
• You orchestrate AI, not just use it. Not "I've tried Copilot," and not just "I use Claude Code." You've run multiple agents in parallel and developed opinions: how to split work so they don't step on each other, where they excel, where they confidently lie, how you structure a repo so they don't wander, and how you verify what comes back at volume.
• Startup energy. Multiple hats, fast cycles, and the judgment to balance "ship it now" against "will this survive contact with real users?"

Experience

3–6 years of professional experience (full-time positions, excluding internships).

Location / How to apply

On-site at our office in HSR Layout, Bangalore.

Apply through this posting, or email us with a link to the best thing you've built.

We are seeking a Senior Full Stack Engineer to join our team in a long-term contractor capacity to continue development of a production-grade platform hosted on AWS and Salesforce.

This application supports policy processing, third-party integrations, compliance workflows, reporting, and intelligent automation capabilities. The ideal candidate is a strong software engineer first, capable of contributing across the full stack while helping scale and evolve the platform.

This role requires someone who can step into an existing system, understand complex workflows quickly, and independently deliver high-quality solutions.

Responsibilities

• Design, develop, and maintain full-stack application features across frontend and backend systems

• Extensive knowledge of Salesforce and how to integrate with it

• Build and support integrations with third-party systems and APIs

• Develop workflow-driven processes using Temporal

• Build scalable APIs and backend services using Python

• Maintain and optimize relational databases using PostgreSQL

• Develop reporting and analytics capabilities using charting libraries

• Contribute to AI-enabled features and integrations within the platform

• Improve CI/CD pipelines and deployment processes

• Participate in architecture discussions and help shape long-term technical direction

• Work closely with business and technical stakeholders to deliver production-ready solutions

Required Qualifications

Engineering

• at least 7+ years of full stack software engineering experience

• Strong proficiency in Python

• Strong frontend development experience with modern web frameworks

• Strong backend API development experience

• Experience designing and building scalable applications

• Strong understanding of software architecture and best practices

• Experience working in complex, integrated systems

Workflow and Orchestration

• Proven experience with Temporal

• Experience building and managing workflow orchestration patterns

• Familiarity with asynchronous processing and event-driven systems

Database and Reporting

• Strong experience with PostgreSQL

• Strong SQL and data modeling experience

• Experience building reporting dashboards and analytics features

• Experience with charting libraries such as Chart.js, D3.js, or Plotly

Third-party software

• Salesforce - integration with the CRM via API, and reporting experience

DevOps

• Experience with CI/CD pipelines

• Familiarity with containerized deployments

• Experience with cloud environments and modern development workflows

Preferred Qualifications

• Experience in insurance, surplus lines, or compliance-based applications

• Experience integrating with third-party vendors and external APIs such as Salesforce

• Experience with AI tooling, LLM integrations, and context engineering

• Experience building intelligent automation features

What We Are Looking For

• Self-driven and highly autonomous

• Strong problem-solving ability

• Comfortable with ownership and accountability

• Able to contribute with minimal supervision

• Strong communication skills in English

• Comfortable working U.S.-based business hours (New York / EST)

Ideal Candidate

A senior full stack engineer who can quickly contribute to an active production system, own features end-to-end, and help expand a platform that sits at the center of complex business workflows and integrations. Send resume with projects and contact information.

About Orenda

Orenda is a fintech-enabled financial services company founded in 2017 and based in Ahmedabad, Gujarat. We work as a corporate DSA and channel partner for leading banks and NBFCs, helping individuals, professionals, and MSMEs access suitable financial solutions across business loans, personal loans, home loans, loan against property, and professional loans.

At Orenda, we combine financial expertise, technology, and streamlined processes to simplify the lending journey. We are building our own lending-tech platform to improve operational efficiency, strengthen lender and partner integrations, and develop technology-driven solutions that support our evolving business needs.

About the role

We're looking for a Lead Software Engineer who enjoys building as much as designing. You'll shape how our systems are architected, write a good share of the code yourself, and lead a team of 3 to 5 engineers, including AI/ML engineers.

This is a hands-on leadership role, not a pure management or architecture position. Your time will be roughly split like this:

Share of time

Leading the team ~30%

Solution design ~30%

Hands-on coding ~30%

Deployment and infrastructure~10%

What you'll work on

Solution design and architecture

• Turning business needs into technical designs that are practical to build and easy to maintain

• Making architecture decisions across services, integrations and data flows

• Estimating, scoping and planning new features with business and product stakeholders

• Shaping the solution design for AI/ML use cases alongside the AI/ML engineers

Engineering and delivery

• Writing production code in Python and Node.js

• Rolling out new features across our internal and partner-facing platforms, including our CRM and partner portal

• Continuously improving existing systems for performance, reliability and code quality

• Reviewing code and setting engineering standards for the team

Infrastructure and cloud

• Maintaining and upgrading our infrastructure, including a planned move to a major cloud platform

• Owning deployments and production stability together with the team

• Working with event-driven and messaging systems (NATS today, Kafka planned)

Team leadership

• Leading and mentoring a team of 3 to 5 engineers

• Planning and prioritising work, unblocking the team, and making sure things ship

• Building a culture of ownership, clear documentation and quality

What we're looking for

• 5 to 8 years of software engineering experience, with hands-on coding in your recent roles

• Strong command of Python and Node.js

• Proven experience designing and building backend systems and microservices that run in production

• Hands-on experience deploying and running workloads on at least one major cloud platform (AWS, Azure or GCP)

• Solid working knowledge of PostgreSQL

• Experience with messaging or event streaming systems such as NATS, Kafka or RabbitMQ

• Experience leading or mentoring a small engineering team

• Comfort estimating effort, breaking down features and planning delivery

• Enough understanding of AI/ML systems to guide their solution design and integration

• Clear communication with both technical and non-technical stakeholders

Good to have

• Experience working at a fintech, lending or financial services company

• Hands-on experience with Kafka

• Experience leading an infrastructure upgrade or cloud migration

• Experience building or scaling CRM or partner-facing portal products

Why Join Us?

• Build a growing lending-tech platform: Play a key role in shaping the technology behind a growing financial services business.
• Own technical decisions: Contribute directly to architecture, engineering standards, and technology direction.
• Stay hands-on: Combine solution design and technical leadership with meaningful coding responsibilities.
• Work with emerging technologies: Collaborate with AI/ML engineers and contribute to evolving platform capabilities.
• Lead and grow a team: Mentor engineers and help build a strong engineering culture as the technology function scales.
• Make a measurable impact: Build systems that improve operational efficiency and support business growth.

We're seeking an experienced Engineer to join our engineering team, handling massive-scale data processing and analytics infrastructure that supports over 1B daily events, 3M+ DAU, and 50k+ hours of content. The ideal candidate will bridge the gap between raw data collection and actionable insights, while supporting our ML initiatives.

Key Responsibilities

• Lead and scale the Infrastructure Pod, setting technical direction for data, platform, and DevOps initiatives.
• Architect and evolve our cloud infrastructure to support 1B+ daily events — ensuring reliability, scalability, and cost efficiency.
• Collaborate with Data Engineering and ML pods to build high-performance pipelines and real-time analytics systems.
• Define and implement SLOs, observability standards, and best practices for uptime, latency, and data reliability.
• Mentor and grow engineers, fostering a culture of technical excellence, ownership, and continuous learning.
• Partner with leadership on long-term architecture and scaling strategy — from infrastructure cost optimization to multi-region availability.
• Lead initiatives on infrastructure automation, deployment pipelines, and platform abstractions to improve developer velocity.
• Own security, compliance, and governance across infrastructure and data systems.

Who You Are

• Previously a Tech Co-founder / Founding Engineer / First Infra Hire who scaled a product from early MVP to significant user or data scale.
• 5–12 years of total experience, with at least 2+ years in leadership or team-building roles.
• Deep experience with cloud infrastructure (AWS/GCP), 
• Experience with containers (Docker, Kubernetes), and IaC tools (Terraform, Pulumi, or CDK).
• Hands-on expertise in data-intensive systems, streaming (Kafka, RabbitMQ, Spark Streaming), and distributed architecture design.
• Proven experience building scalable CI/CD pipelines, observability stacks (Prometheus, Grafana, ELK), and infrastructure for data and ML workloads.
• Comfortable being hands-on when needed — reviewing design docs, debugging issues, or optimizing infrastructure.
• Strong system design and problem-solving skills; understands trade-offs between speed, cost, and scalability.
• Passionate about building teams, not just systems — can recruit, mentor, and inspire engineers.

Preferred Skills

• Experience managing infra-heavy or data-focused teams.
• Familiarity with real-time streaming architectures.
• Exposure to ML infrastructure, data governance, or feature stores.
• Prior experience in the OTT / streaming / consumer platform domain is a plus.
• Contributions to open-source infra/data tools or strong engineering community presence.

What We Offer

• Opportunity to build and scale infrastructure from the ground up, with full ownership and autonomy.
• High-impact leadership role shaping our data and platform backbone.
• Competitive compensation + ESOPs.
• Continuous learning budget and certification support.
• A team that values velocity, clarity, and craftsmanship.

Success Metrics

• Reduction in infra cost per active user and event processed.
• Increase in developer velocity (faster pipeline deployments, reduced MTTR).
• High system availability and data reliability SLAs met.
• Successful rollout of infra automation and observability frameworks.
• Team growth, retention, and technical quality.

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