SDE IV

About the company

The client is the home base for hardware engineers. They give the teams building robots, rockets, medical devices, and the next generation of physical products a single place to move fast without breaking things, turning CAD chaos into a system of record engineers actually love to work in. We're profitable, post-Series A, and growing our Hyderabad engineering team.

About the role

We're looking for a tech lead to set the technical direction for a growing team and raise the bar for everyone around them. This is a hands-on leadership role: you'll still write production code, but your largest impact comes through architecture, mentorship, and the standards you instill. You own outcomes for a team, not just your own commits. 

What you'll do

• Lead the technical direction of a team building across our TypeScript/React + Node.js + AWS stack
• Drive architecture decisions, document tradeoffs, and align the team on a clear technical path Mentor engineers through code review, pairing, and guidance, growing them toward strong production ownership
• Set and uphold standards for code quality, testing, and operational rigor
• Stay hands-on: write production code on the highest-leverage and hardest problems
• Partner with product and leadership to scope work, manage technical risk, and deliver predictably
• Be accountable for the reliability and maturity of the systems your team owns in production

What we're looking for

• Demonstrated technical leadership: you've set direction for a team and elevated those around you
• Strong full-stack proficiency in TypeScript, React, and Node.js, plus solid AWS depth
• A track record of shipping to production and owning systems in operation, and of holding a team to that same standard
• Strong architectural judgment: you decompose ambiguous problems, weigh tradeoffs, and make decisions others can build on
• Excellent communication: you keep your team aligned and stakeholders informed, and you surface risk early
• Comfort leading in a fast-paced, high-ownership early-stage environment 

Why choose us?

• The teams building advanced hardware and the robots, machines, and devices shaping the future run
• Direct access to founders; you'll help shape product and engineering direction, not just execute tickets
• Fast feedback loops: what you build is in front of customers in days, not quarters
• Profitable at Series A, so you get startup upside without the constant fundraising-survival anxiety
• Competitive compensation and meaningful equity
• Bi-yearly appraisal cycles
• Upto 20% Bonus based on performance
• Monthly Swiggy vouchers
• Flexibility with work hours

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

About the role

You will be a pivotal member of the leadership team, responsible for driving the company's product and platform strategy while overseeing engineering excellence across AI, data, platform, DevOps and infrastructure. This is a mission-critical role for an engineering leader who is both strategic and hands-on, and who can build scalable technologies for global enterprise clients in a fast-paced innovation ecosystem.

Reports to: CEO · Location: Bengaluru, India — hybrid, 3 days a week in office

What you will do

Technology & product leadership

• Define and drive the technology vision, architecture and long-term platform roadmap.
• Oversee the architecture, design and delivery of highly scalable enterprise systems.
• Ensure engineering excellence, velocity and reliability across the product lifecycle.

Engineering & platform management

• Lead platform engineering, product technology, DevOps, infrastructure and Quality Engineering.
• Build robust cloud-native systems using the Azure, AWS and GCP ecosystems.
• Oversee operational effectiveness, including uptime, production reliability and cost optimisation.

Innovation & AI strategy

• Spearhead Mission AI by developing scalable, production-grade AI/ML and GenAI capabilities.
• Own the GenAI/LLM solutions architecture.
• Core specialisation in AI agents and autonomous workflows, data extraction and intelligent automation.
• Direct hands-on architectural oversight of large language models, applied AI and multi-layered deep learning products.
• Extensive expertise in building intelligent document automation systems — similar in complexity to patent parsing, legal workflow automation and structured decision intelligence tools.

Technical leadership

• A proven track record overseeing product architecture, tech strategy and cross-functional engineering execution across core full-stack and AI platforms.
• Collaborate with executive leadership on business strategy, client requirements and product delivery.
• Build, mentor and scale high-performing engineering teams with a growth mindset.
• Establish a strong technology culture grounded in ownership, innovation and continuous learning.

What success looks like

• Mission AI: build a world-class AI system leveraging GenAI, ML and enterprise-grade data engineering.
• Hyper-scaling: architect and scale the platform to match global industry leaders in the IP space.
• Culture building: develop a strong engineering organisation with high ownership, performance and innovation DNA.

Qualifications & experience

• Preferably under 15 years of enterprise software engineering experience across B2B SaaS or technology-first companies; fewer is fine for an exceptional engineer.
• A proven track record of taking early-stage AI/ML prototypes and scaling them into robust enterprise SaaS platforms featuring multi-agent orchestration, complex workflows and decision intelligence.
• Experienced in building and mentoring agile, lean startup teams of full-stack and machine learning engineers from the ground up.
• Proven leadership in defining and executing technology strategy and platform roadmaps.
• Extensive cloud-native engineering experience with Azure, AWS and GCP.

Technical expertise

• Strong full-stack engineering background (Java, Python, JavaScript frameworks).
• Expertise with JS frameworks such as React, Angular and Node.js.
• Experience building and scaling distributed systems and microservices.
• Strong knowledge of databases (SQL, NoSQL), data modelling and unstructured data management.
• Strong understanding of Agile methodologies and tools (Atlassian, Git, CI/CD pipelines).

Behavioural & leadership competencies

• Product and delivery management expertise, end to end, including delivery and customer support.
• Excellent communication, with the ability to influence executive stakeholders.
• High technical proficiency combined with strong business acumen.
• Strong analytical and decision-making skills.

Responsibilities

• Engineering technical lead for the AI Garage team which responsible for developing AI/ML systems and Agentic solutions in HR domain 
• Drive engineering excellence for the AI Garage team 
• Provide technical leadership in regards to immediate and complex technical problems to leads of associated teams.
• Influence and Design and build scalable Agentic systems in HR domain. 
• Collaborate with AI Garage Leads ( Eng Managers, Product Managers and AI strategist ) and stakeholders to understand their needs and translate them into technical solutions.
• Stay up-to-date with the latest trends in Agentic and AIML engineering.

Required Skill :

• Master's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience
• 8+ years of experience in software development, including proficiency in one or more programming languages, artificial intelligence, machine learning algorithms and tools, and Generative AI (Large Language Models, Multi-Model, etc.)
• Design and implement scalable AI solutions for Enterprises.Experience in Building and rolling out AI and agentic solutions for Global Enterprises
• Multi-Agent Systems: Handle collaboration, memory persistence, and dynamic planning using frameworks like LangGraph, CrewAI, or AutoGen.
• Optimization & Evaluation: Track agent trajectories, manage cost/latency, and implement LLM-as-a-judge frameworks (e.g., Phoenix, LangSmith).
• Safety & Compliance: Prompt injection mitigation, sandboxed code execution, and human-in-the-loop (HITL) checkpoints.
• Experience with offline,online and RL based validation
• Metrics Selection: Knowing which evaluation metric matches specific business constraints (e.g., using Precision/Recall or Area Under the ROC Curve (AUC) rather than basic Accuracy on an imbalanced classification dataset).
• Good understanding of the Bias-Variance tradeoff, Overfitting vs. Underfitting, and practical techniques to fix them (L1/L2 Regularization, Dropout, Early Stopping). 
• Dynamic Context Compaction: Skills in designing algorithms that programmatically truncate, summarize, or extract semantic milestones from a running conversation log so the agent doesn't suffer from "lost in the middle" phenomena during long-horizon tasks.
• Advanced Reasoning Frameworks: Implementing and customizing structural execution patterns like ReAct (Reason + Act), Tree of Thoughts (ToT), and Plan-and-Solve loops, giving models the cognitive scaffolding to break down vague goals into deterministic DAGs 
• Evidence in runtime layers that scan user inputs for prompt injection or jailbreak attempts designed to hijack an agent’s system tools, alongside strictly isolating tool execution environments
• Experience with LoRA or SFT and reasoning 

Read This Before Anything Else

We have 6 developers who can ship. What we don't have is someone who turns that into a real engineering function: real architecture, real leverage, real AI-driven advantage. If that gap sounds like an opportunity rather than a headache, you're in the right place. If it sounds like a lot of undefined work with no playbook handed to you, this one probably isn't for you. That's completely okay. There are plenty of great roles that fit differently.

About CraftMyPlate

CraftMyPlate is Hyderabad's go-to platform for food experiences for micro-events: house parties, birthdays, office celebrations, festive gatherings, and more. We're building the operating system for how India discovers, customises, and orders food for smaller events. We're backed by established founders and investors, and we're funded and growing fast. The next phase of that growth runs through engineering.

Where We Stand

Some numbers, because they matter more than adjectives. Order volume has grown 50x in two years, and we're compounding at roughly 3x year over year, without giving up equity to fund it. That means the business runs on its own economics. The growth is real demand, not runway bought with dilution, and every efficient architectural decision this role makes directly protects that.

Most people size up an opportunity by asking what's going to change in ten years. The more useful question, and the one this company is built around, is what won't change. People will keep gathering. They'll keep celebrating, hosting, and marking festivals, in 10 years and in 20. That permanence is the bet. You're not building infrastructure for a trend cycle. You're building for a category that outlasts the current AI wave, the next funding round, and probably us too.

The Technical Reality

Here's an honest read of the engineering problem, not a sanitized version of it.

Event-driven commerce doesn't scale like typical e-commerce. Demand isn't smooth, it's spiky: weekends, festival calendars, and event dates create real load concentration, and each order is tied to a hard deadline that can't slip the way a shipped package can. That has direct architectural consequences: systems need to handle bursty, unpredictable traffic without paying for idle capacity the rest of the time, which is exactly why we're serverless-first on AWS rather than running a fixed fleet sized for peak.

Underneath that, every order touches multiple systems that have to stay consistent: kitchen and vendor fulfillment status, inventory across partners, payment gateway settlement, and refunds, often in real time and often across more than one vendor for a single event. Getting that consistency right across SQL and NoSQL stores, without it becoming a source of support tickets and manual reconciliation, is a real architecture problem, not a CRUD problem.

The AI-agent layer is the next lever, and it's a business lever as much as a technical one. Every workflow we can hand to a well-orchestrated agent instead of a new hire is a workflow that scales without adding headcount, which is exactly how a company grows 3x a year without diluting equity to fund the team behind it. That's why agent orchestration across multiple LLMs, using LangGraph, sits in the "go deep" tier of this role rather than being a nice-to-have.

You'll likely find some of this framing right and some of it worth challenging once you're actually in the codebase. That's expected, and honestly preferred over someone who just nods along.

Why This Role Exists

You'll be the most senior technical person in the company, reporting directly to the founder. Not a manager brought in to run standups. An owner. You set the architecture, you write code yourself, and you make the team materially better. You also own where AI and automation take this company next, starting with our first in-house AI agent product (details shared in the interview), and expanding from there into how the company runs, department by department: HR, finance, marketing, design, development, all sitting on an engineering layer that you design.

If you've outgrown a role where you plan but don't build, or where good ideas die in a committee, this is built to be the opposite of that.

What You'll Own

• Architecture, end to end. Scalable, cost-efficient systems from day one, not "fix it later" engineering. You own the decisions and their long-term consequences.
• Hands-on building. You are still writing code and shipping. This isn't a seat where you review other people's work all day. You lead by building.
• The engineering team. Directly manage, mentor, and level up our 6 developers. Build the technical bar, the review culture, and the calibration that lets the team ship independently.
• The AI-agent roadmap. Own the architecture behind our first AI agent product, then the broader strategy for AI agents and automation across every function in the company, with engineering as the layer underneath all of it.
• Team scaling. Build the next layer of leads under you so execution quality scales without you being the bottleneck.
• Technical accountability. When something breaks, you fix it. You don't escalate and wait.

Our Stack, and the Depth We Expect

Not everything on this list needs the same level of mastery. Some of it you need to own at an architectural level. The rest you need to be strong enough to build yourself, direct the team on, or delegate to AI agents with confidence.

Go deep here. This is where the real architecture decisions live, and where the business impact is highest:

• AWS, serverless first. You should be genuinely well versed in AWS application development, not just "have used AWS." You should be able to design and guide serverless architecture (Lambda, API Gateway, DynamoDB, Step Functions, and similar) as our default way of building, because our demand curve is spiky by nature and fixed infrastructure is money left on the table.
• TypeScript, our primary language across backend and frontend.
• Agent orchestration across multiple LLMs, using LangGraph. This is core to our AI roadmap and our path to scaling operations without scaling headcount. You own how it's architected, not just how it's used.

Working proficiency. Build it yourself, direct the team, or hand it to an AI agent and know if the output is right.

This Is You If

• You've built and shipped real production systems yourself, not just reviewed other people's architecture from a distance.
• You go deep wherever the problem is, and you're comfortable owning the exact stack described above, not just "full-stack" in the abstract.
• You've made engineers around you measurably better, whether or not you've held the title for it yet.
• You're already using AI coding tools and agents seriously, like Claude, Cursor, or similar tools, as part of how you build, not as something you tried once. We'll likely explore this together in the interview.
• You have a bias toward leverage over hours. You'd rather automate or systematize a problem than grind through it. But when something's live and needs to be done right, you see it through completely, with no half-finished work.
• You want to build something for years, not land somewhere comfortable. We'll know the difference from how you talk about your last three years.

This Might Not Be the Right Fit If

• You'd prefer a stable, well-defined role with clear boundaries and someone else making the calls. That's a fair thing to want, just not what this is.
• You'd rather receive direction than bring us architecture and AI strategy yourself.
• You haven't yet gotten hands-on with AI coding tools in your daily work.
• You're drawn more to the title than the work behind it.

If none of that sounds like you, we'd love to hear from you.

Requirements

• 5 to 7 years of experience in software engineering, with real ownership of architecture-level decisions, not just feature delivery.
• Prior experience leading or mentoring engineers, formally or informally.
• Tier-1 or Tier-1+ engineering college strongly preferred (IIT, BITS, top NIT tier, or equivalent). We'll consider other institutions only with clearly commendable, verifiable work: real systems you can walk us through in depth, strong open-source contributions, or a track record that speaks for itself. Pedigree is a proxy for speed, not a checkbox. We test for the underlying ability regardless.
• Comfortable in an early-stage environment: undefined problems, few processes, and the expectation that you help define both.

Compensation

Competitive, with equity. We're formalizing a structured ESOP program alongside this hire. Specific numbers are discussed directly in later interview rounds.

If reading this got you a little excited about what you'd build here, we'd genuinely love to talk. If it didn't quite land, no hard feelings. We just want the right fit for both sides.

Staff Engineer - AI:

Location : India, Remote

Job Description

Egnyte is seeking an experienced Staff Software Engineer to join our Engineering department. The Engineering department builds large distributed components and services that run Egnyte's Cloud Platform. Our code serves billions of requests per day with sub-second latency in a fault-tolerant environment. We process and analyze millions of files and events daily. Some of the responsibilities for this department include Egnyte's Cloud File System, Content Classification, Content Lifecycle Management, User Behavior Analysis, Object Store, Metadata Stores, Search Systems, Recommendations Systems, Synchronization, and intelligent caching of multi-petabyte datasets. We are looking for candidates with a shared passion for building large-scale distributed systems and a keen sense for tackling complexities that come with scaling through multiple orders of magnitude.

In this role, you will (But are not limited to):

• Design and develop highly scalable and resilient cloud architecture that seamlessly integrates with on-premises systems
• Drive the team’s goals and technical direction to find and pursue technical opportunities that make Egnyte’s cloud platform more efficient
• Effectively communicate complex design and architecture details
• Understand company and industry-wide trends to help develop new technologies
• Conceptualize, develop, and implement changes that prevent key systems from becoming unreliable, under-utilized, or unsupported
• Own all aspects of critical software projects from design to implementation, QA, deployment, and monitoring

Qualifications

• BS, MS, or PhD. in Computer Science or related technical field, or equivalent practical experience
• 8-15 years of professional experience in engineering with a history of technical innovation
• Experience providing technical leadership to engineers

Bonus Qualifications (Good to Have)

• The breadth of knowledge across infrastructure domains, with the ability to reason about everything from data center machine software to database solutions to machine learning infrastructure to front-end web or mobile applications
• Demonstrated success in designing and developing large-scale, complex systems
• Expertise with multi-tenant, highly complex, cloud solutions; experience with Hybrid and/or on-premises solutions desired

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

Technical Architect – Product Engineering

Experience: 15+ Years

Location: Pune, India

Employment Type: Full-time

Desired Skills: Python, Technical Architecture, AWS, Microservices, SaaS / Multi-tenant Architecture, Kubernetes, System Design

About the Role

We are looking for a Senior Technical Architect to lead the architecture, design, and technical evolution of an enterprise SaaS product. This is a hands-on leadership role requiring deep technical expertise, strong product engineering experience, and the ability to build scalable, secure, and high-performance platforms.

The ideal candidate should be passionate about solving complex engineering problems, driving innovation, mentoring development teams, and effectively leveraging AI to accelerate software development.

Key Responsibilities

• Own the overall product architecture and technical roadmap.
• Design and build scalable, secure, and highly available enterprise applications.
• Lead the design and implementation of new product features from concept to production.
• Remain hands-on with coding and contribute to critical product components.
• Drive architecture reviews, code quality, performance optimization, and engineering best practices.
• Lead cloud architecture, security, scalability, and DevOps initiatives.
• Evaluate and adopt modern technologies to improve product capabilities and engineering efficiency.
• Leverage AI tools (ChatGPT, GitHub Copilot, Cursor, Claude, etc.) to accelerate software development, code reviews, testing, documentation, debugging, and productivity.

Required Skills & Qualifications

• 15+ years of software product engineering experience with at least 5 years in a Technical Architect role.
• Strong hands-on expertise in Python and modern backend frameworks.
• Deep experience with AWS services and cloud-native application architecture.
• Strong understanding of DevOps, CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation), Docker, Kubernetes, and container orchestration.
• Experience designing microservices, REST APIs, event-driven architectures, and distributed systems.
• Strong knowledge of SQL and NoSQL databases.
• Experience with scalable SaaS platforms, multi-tenant architectures, and secure application design.
• Excellent understanding of software design patterns, performance tuning, observability, and system reliability.
• Strong analytical, problem-solving, and decision-making skills.

We are looking for a Senior Software Engineer who will be driving architectural direction, multi-team initiatives, and the development of highly scalable distributed systems. You will partner with Product, Architecture, DevOps and cross-functional engineering teams to deliver impactful technology solutions across a complex digital ecosystem. You will independently define and deliver large-scale, multi-phase projects, mentor engineers, and shape technical strategy. The role also includes leveraging LLMs and GenAI-driven tools to enhance engineering productivity, reduce cycle time, and build the next generation of internal developer experience tools.

Technical Leadership • Drive technical strategy and architecture for complex distributed systems and core platform components. • Own end-to-end delivery of high-impact, multi-team engineering initiatives. • Translate ambiguous business requirements into clear, pragmatic technical solutions. Public • Define technical roadmaps, sequence projects into phases, and ensure timely execution across teams.

Software Engineering & System Design • Architect, develop, and optimize microservices using Java, Spring Boot, Spring Cloud. • Design scalable, resilient, secure cloud-native applications using Azure/AWS. • Lead system design reviews, architecture discussions, and technical deep dives. • Solve complex cross-system issues through deep debugging, performance tuning, and root cause analysis. • Build frameworks and shared libraries to accelerate development across squads.

AI & Engineering Productivity • Champion adoption of AI-assisted development practices and LLM/GenAI tools across engineering teams to enhance workflows, improve cycle time, and automate routine tasks. • Define clear guidelines, training, and standards for effective and secure use of AI tools, including prompt engineering, code generation, and review expectations. •

Integrate AI-driven capabilities such as code generation, unit test creation, log analysis, documentation summarization, and code review assistance into the development workflow. • Establish and enforce engineering best practices for AI-generated code, including human-in-the-loop reviews, coding standards, test automation, secure coding, and design-first development. • Measure and optimize engineering productivity using AI-related metrics (cycle time, PR throughput, AI-code adoption, defect escape rate, developer satisfaction) and continuously identify opportunities to reduce bottlenecks with AI.

Collaboration & Cross-Functional Impact • Work closely with Product Owners, Architects, QE, DevOps, and peer engineering teams.

• Communicate technical trade-offs, risks, and decisions clearly to non-technical stakeholders. • Coordinate across teams to resolve dependencies and align on architectural standards.

• Influence technical direction beyond your immediate team. Team Leadership & Mentoring

• Mentor engineers across multiple teams, guiding them in design, coding, debugging, and best practices.

• Participate actively in hiring and talent development.

• Raise the engineering bar through code reviews, design critiques, and technical leadership.

• Help define and uphold engineering best practices, coding standards, and architectural principles. Ownership & Operational Excellence

• Take full ownership of systems from development to deployment, monitoring, and maintenance.

• Ensure engineering deliverables meet performance, reliability, and security criteria.

• Proactively identify areas for improvement and propose scalable, maintainable solutions.

• Lead incident response, post-mortems, and continuous improvement initiatives.  

Main Skills

Experience applying LLMs/GenAI to improve engineering productivity and developer workflows.

• Prompt engineering experience and familiarity with integrating models into applications.

• Experience with Domain-Driven Design, event-driven systems, CQRS, or enterprise integration patterns.

• Familiarity with Linux systems and container-based deployment architectures.

• Experience with application servers such as Tomcat.

• Contributions to internal platforms or open-source projects.

• Strong leadership qualities with the ability to influence without authority.

• High levels of self-motivation, ownership, and drive.

• Critical thinking abilities and a strong problem-solving mindset.

• Excellent team collaboration skills and a positive, proactive attitude.

Deep expertise in Java, J2EE, Spring, Spring Boot, Spring Cloud, and building microservices-based architectures. 

Hands-on experience with Docker, Kubernetes / OpenShift, and CI/CD pipelines.

• Strong knowledge of working with databases: Oracle, MySQL, MongoDB, Cassandra, etc.

• Experience designing and scaling systems on Azure, AWS, or Google Cloud.

• Excellent problem-solving skills, debugging capabilities, and system-level thinking. 

Tech Architect/Lead – Node.js ( React & Angular) (Full Stack)

Experience: 8–15 years

Role Type: Technical Leadership / Hands-on Architecture & Development

Role Overview

We are looking for a hands-on Technical Architect / Tech Lead with strong expertise in Node.js and Angular/React who can own end-to-end technical delivery, lead an engineering team, make architecture and design decisions, and work closely with Product, QA, and DevOps teams.

The ideal candidate should have strong product development experience and be capable of taking ownership from requirements and architecture through development, deployment, and production support.

Key Responsibilities

• Own end-to-end technical delivery of applications/modules, ensuring quality, timelines, scalability, and maintainability.
• Design and evolve application architecture using Node.js, React, Angular TypeScript/JavaScript, and modern architectural patterns.
• Translate product/business requirements into technical architecture, system design, APIs, data flows, and implementation plans.
• Make key architecture and technology decisions, conduct design/code reviews, and establish engineering best practices.
• Remain hands-on and contribute to the development of critical and complex features.
• Lead and mentor the engineering team, provide technical direction, remove technical blockers, and drive engineering quality.
• Design and develop scalable backend services, REST APIs, integrations, and frontend applications.
• Define appropriate deployment, release, and environment strategies in collaboration with DevOps.
• Work with DevOps/Cloud teams on CI/CD, Docker/containerization, configuration, logging, monitoring, scalability, and production deployments.
• Identify and proactively address technical risks, performance issues, security concerns, and scalability challenges.
• Collaborate closely with Product, QA, Business, and DevOps stakeholders throughout the SDLC.
• Ensure effective practices around code quality, testing, version control, release management, and production readiness.

Must-Have Technical Skills

Backend

• Strong hands-on expertise in Node.js
• TypeScript / JavaScript
• REST API and service-oriented/microservices architecture
• API security, authentication/authorization, integrations
• Asynchronous and event-driven programming
• Strong understanding of databases such as PostgreSQL, MySQL, MongoDB, or equivalent

Frontend

• Strong hands-on expertise in Angular & React
• React application architecture and component design
• State management and frontend design patterns
• Modern JavaScript/TypeScript
• Frontend performance and responsive application development

Architecture & System Design

• Strong experience in application architecture and system design
• Design patterns, scalability, performance, security, and maintainability
• Experience designing distributed/scalable applications and integrations
• Ability to evaluate technology options and make pragmatic architecture decisions

DevOps / Cloud – Working Knowledge

• Good understanding of CI/CD and deployment strategies
• Git and branching strategies
• Docker/containerization/Kubernetes concepts
• Environment/configuration management
• Logging, monitoring, observability, and production troubleshooting
• Working knowledge of AWS, Azure, or Google Cloud
• Ability to effectively collaborate with DevOps/Cloud teams

Scripting

• Good scripting/automation skills using JavaScript/TypeScript, Shell, Python, or similar

Leadership & Product Skills

• Proven experience leading engineering teams and mentoring developers.
• Strong ownership of product development and technical delivery.
• Ability to work with Product/Business teams and convert requirements into technical solutions.
• Strong problem-solving and decision-making skills.
• Excellent communication and stakeholder-management skills.
• Ability to balance delivery timelines, technical debt, quality, scalability, and maintainability.
• Experience working in Agile/Scrum product development environments.

Next

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