Principal Engineer

Principal Enterprise GenAI / Agentic AI Architect - (Freelance) 

Positions: 1

Experience: Ideally 10–16 years overall, with significant recent hands-on GenAI/LLM architecture experience.

Mission

Own the end-to-end architecture across RAG, Agentic AI, enterprise integrations, model serving, security, evaluation, observability and production deployment.

This should not be a PowerPoint-only architect. We need someone technically deep enough to review code, challenge engineering decisions, troubleshoot RAG/agent behaviour and interact credibly with customer architecture/security/platform teams.

Mandatory capabilities

• Enterprise GenAI architecture
• Production RAG
• Agentic AI architecture
• Python
• LangGraph or comparable stateful orchestration
• Tool/function calling
• Human-in-the-loop workflows
• Vector databases
• Embeddings/reranking
• LLM/RAG/agent evaluation
• REST APIs/microservices
• Enterprise IAM
• RBAC/ABAC
• AI security and prompt-injection mitigation
• Kubernetes
• CI/CD and LLMOps/MLOps
• Enterprise observability

Highly desirable

OpenShift/OpenShift AI, NVIDIA NIM, KServe, NVIDIA GPU Operator, open-weight LLM deployment, ServiceNow, Splunk, Microsoft Graph and previous banking/financial-services experience.

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

Cognizant is one of the world's leading professional services companies, transforming clients' business, operating, and technology models for the digital era. Our unique industry-based, consultative approach helps clients envision, build, and run more innovative and efficient businesses. Headquartered in the U.S., Cognizant (a member of the NASDAQ-100 and one of Forbes World's Best Employers 2025) is consistently listed among the most admired companies in the world. 

This role is part of Cognizant IOA (Intuitive Operations and Automation) — and more specifically, a product team with its own origin story. We started as Matterway, a German startup building automation software from scratch. We were acquired by Cognizant, but we kept our team, our culture, our pace, and our way of working. We move like a startup, think like a startup, and now do it with the backing of a global company. 

We combine human expertise with intelligent automation, ML operations, and digital experience solutions to help technology and digital-native companies build smarter, more adaptive operating models. 

What's the opportunity? 

We are looking for Senior Product Engineers to join our team. We're a tight crew of 5 senior engineers, from different corners of the world. We're hiring 3 more people, and those people will shape what this team becomes. 

We're building a platform to support the agentification of our operations. You'll work across a suite of products including a cloud platform for process optimization, desktop application, browser extension, and specialized AI agents. 

This is genuinely frontier work: we don't follow AI trends, we implement them. New model drops on a Monday; we've prototyped with it by Wednesday. 

We believe this is the most exciting time to join. Be part of the founding R&D talent in this area and help set the technical bar for everything that comes next. 

What will you be doing? 

Your day-to-day responsibilities: 

• Design and evolve the core architecture of our platform 
• Set technical standards and take ownership of complex projects end-to-end 
• Work on a well-architected, fast-evolving TypeScript codebase using technologies such as React, Node.js, Electron, and GraphQL 
• Collaborate with product managers, designers, and engineers to solve challenging technical and business problems, with real autonomy 
• Participate in the full development lifecycle: scoping, design, estimation, coding, testing, debugging, code reviews, maintenance, and support 
• Evaluate and implement proofs of concept using the latest AI tools and models 

You will know you're successful if: 

• You develop projects independently until they deliver their intended business value 
• You keep top-notch software quality standards about design, implementation, and documentation 
• You're the person who brings something new to the team's radar, a model, a technique, a tool, before anyone else has heard of it 

What makes you a great fit 

Must-haves: 

• Excellent English (C1+) with exceptional written and verbal communication 
• Strong proficiency with TypeScript across frontend and backend, including building and maintaining Node.js-based services 
• Experience in frontend development using modern frameworks such as Vue.js or React 
• Knowledge of any E2E testing framework such as Playwright, Puppeteer, Selenium, Cypress 
• Ability to work independently and take ownership of deliverables 
• Strong technical fundamentals, genuine intellectual curiosity, and a drive to keep getting better 
• You follow AI closely, not just as a user but as someone who reads the papers, watches the releases, and has opinions. You're excited about where this is going and want to be building at the edge of it 

Nice-to-haves: 

• Familiarity with AI-coding tooling (Claude Code, Cursor, OpenCode, etc.) 
• Experience with cloud infrastructure (AWS, Azure or GCP) and infra-as-code deployment 
• Having built or maintained CI/CD pipelines or workflows, especially GitHub actions 

Why join us? 

• Be at the cutting edge of AI agents and applying LLMs to real-world use cases, not in theory but in production 
• Work on hard problems with high agency: your ideas get heard; your decisions get shipped 
• Join a small but growing internationally distributed team. 
• giving you real influence over how it evolves 
• The resources of a global company with the speed and culture of a startup 
• Remote-first set-up, with the option to work from one of our 13 locations in India: Chennai, Bangalore, Hyderabad, Pune, Mumbai, Gurgaon, Noida, Kolkata, Kochi, Coimbatore, Bhubaneswar, Mangalore, and Indore 
• Flexible working hours 
• Collaborative, pragmatic engineering culture focused on outcomes 
• Fast-growing team within Cognizant, with access to global resources and real career opportunities 

We are looking for an Engineering Lead to own the entire technology stack — from onboarding and underwriting to disbursals, repayments, and collections — and to build the engineering function into something genuinely AI-native. 

What You'll Own 

● Full tech stack: backend, frontend, infrastructure, integrations, and data pipelines 

● Real-time underwriting and decisioning systems 

● LOS/LMS architecture — onboarding, disbursals, repayments, and collections

● Integrations with bureaus, KYC providers, account aggregators, and payment gateways 

● Reconciliation systems — disbursement, repayment, and NACH reconciliation end-to-end 

● AWS infrastructure: scaling, reliability, uptime, and cloud cost ownership ● Data infrastructure for the credit and risk team — feature pipelines, model serving, experiment infrastructure 

● Engineering leadership: hiring, sprint planning, code reviews, and execution standards 

● Compliance systems: RBI guidelines, DPDP, KYC/AML, e-NACH, e-sign 

AI-Native Engineering 

This is a core part of the role, not a bonus. You will build a machine-readable knowledge base of the entire codebase — architecture, data models, service contracts, coding standards, decision history — so that AI agents working on code have the context to produce accurate, consistent output. You will build skills for code review, developer onboarding, and recurring engineering workflows. You will build a code review pipeline where agents do the first pass on every pull request. The knowledge base and the skills improve over time as the team grows and the product evolves. 

What We're Looking For 

● 7+ years in software engineering, with at least 2 years leading teams or architecture

● Strong hands-on experience with Python, Django, and React Native

● Deep expertise in AWS and cloud-native architecture 

● Experience with both SQL and NoSQL databases 

● Strong understanding of distributed systems, microservices, and API design

● Experience owning reconciliation or payment flow infrastructure in a lending or payments context

● Prior experience in fintech / NBFC / digital lending — mandatory

● Strong understanding of the full loan lifecycle — mandatory 

● You have used LLMs seriously as engineering tools and have strong opinions about what makes AI-assisted development produce good output versus mediocre output 

Bonus: Kubernetes / Kafka, AI/ML-driven underwriting, Account Aggregator framework, e-NACH / e-Sign / Video KYC integrations 

What Success Looks Like 

● scales with strong uptime, performance, and reliability

● Reconciliation runs cleanly — no financial discrepancies surface late ● A new engineer joins and is writing standard, correct code within their first week

● The credit team is never blocked on an engineering dependency 

● Engineering health metrics are tracked and visibly improving 

● AI agents are doing the structured first pass on code reviews, and the system gets smarter over time 

PRINCIPAL AI ENGINEER @ METADOME.AI

Company Description

Metadome.ai builds frontier AI models that transform text, drawings, and CAD into production-ready, interactive 3D experiences. The company advances a full generative pipeline—text-to-CAD, 2D-to-3D

reconstruction, CAD completion and harmonization, and real-time interactive rendering—engineered for the precision required in the physical world. Its technology currently powers the modernization of

OEM aftersales for more than 30 automotive and heavy-equipment manufacturers worldwide, delivering accurate, scalable, and fast 3D solutions. Metadome.ai’s platform enables shoppable 3D parts, step-by-step repair animations, and a headless API that feeds consistent 3D assets into commerce, dealer, training, and service systems. The broader mission is to allow anyone to move from an idea, drawing, or specification to a production-grade 3D model and beyond in seconds.

Role Description

As a Principal AI Engineer — Generative CAD & 3D, you will lead the design, development, and deployment of advanced AI models that convert text, 2D drawings, and CAD files into engineering-grade 3D content. You will architect end-to-end generative pipelines, including

text-to-CAD, 2D-to-3D reconstruction, CAD completion, and real-time rendering, collaborating closely with product, design, and engineering teams to ship robust production systems. Day-to-day, you will experiment with novel neural network architectures, optimize model performance on large-scale CAD datasets, write high-quality production code, and guide the integration of AI services into customer-facing platforms. You will mentor other engineers, establish best practices for AI development, and contribute to technical strategy and roadmap. This is a full-time, hybrid role based in Bengaluru, with a mix of on-site collaboration and work-from-home flexibility.

Qualifications

• Strong foundation in Computer Science and Software Development, including data structures, algorithms, system design, and production-grade coding in languages such as Python, C++, or similar.
• Deep expertise in Neural Networks and Pattern Recognition, with hands-on experience designing, training, and deploying modern deep learning architectures for complex, high-dimensional data.
• Experience with Natural Language Processing (NLP), including working with text encoders, multimodal models, and integrating language understanding into generative workflows.
• Advanced degree (Master’s or PhD) in Computer Science, Electrical Engineering, Applied Mathematics, or a related field, or equivalent practical experience in AI/ML research and engineering.
• Background in 3D geometry, CAD, computer graphics, or related domains, with familiarity in 3D representations, mesh processing, and rendering pipelines.

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

Title                                 : Senior GenAI Engineer — RAG (Full-Stack)

Experience                    : 5+ years

Location                         : Remote

Work type                      : Chennai - Work from Office/ Remote – Other locations

Employment Type      : Full Time

Notice Period               : Immediate

Work Day                       :Mon to Fri

Key Responsibilities:

• RAG pipeline end to end: ingestion integration, hybrid retrieval with reranking, prompt/context strategy, citation resolution, refusal behavior
• Permission-aware retrieval: source ACL mapping (SharePoint/Entra, Confluence) to fail-closed retrieval filters; zero-leakage test suite partnership with QA
• Vector database design and operations (Milvus or pgvector): schema, metadata filters, sync, performance
• Full-stack product build: React/TypeScript chat and citation experience, Python/FastAPI services, REST APIs, SSO/OIDC integration, admin configuration UI
• Evaluation-driven development: retrieval precision, faithfulness, and citation-accuracy metrics as the daily working loop; A/B testing of retrieval and prompt variants
• Latency engineering to the 3–5s first-token / ~15s complete-answer targets at concurrency

Technical Skills:

• 5+ years software engineering with 2+ years building RAG/LLM applications in production — with real users and real quality metrics, not notebooks
• Deep retrieval craft: chunking strategy, embeddings, hybrid search, rerankers; you can explain why retrieval fails and how you measured the fix
• Genuine full-stack evidence: shipped React/TypeScript front ends AND Python back-end services in production; API design; OIDC/SAML integration
• Vector database production experience (Milvus, pgvector, Weaviate, or equivalent) including permission/metadata filtering
• Evaluation fluency: has built or operated a retrieval/answer quality harness with numeric thresholds

Strongly Preferred:

• Permission-aware/multi-tenant retrieval specifically; Microsoft Graph API; NIM/OpenAI-compatible serving endpoints; streaming UX; enterprise design systems; banking content domains

About Ampera: 

Ampera Technologies, a purpose driven Digital IT Services with primary focus on supporting our client with their Data, AI / ML, Accessibility and other Digital IT needs. We also ensure that equal opportunities are provided to Persons with Disabilities Talent. Ampera Technologies has its Global Headquarters in Chicago, USA and its Global Delivery Center is based out of Chennai, India. We are actively expanding our Tech Delivery team in Chennai and across India. We offer exciting benefits for our teams, such as 1) Hybrid and Remote work options available, 2) Opportunity to work directly with our Global Enterprise Clients, 3) Opportunity to learn and implement evolving Technologies, 4) Comprehensive healthcare, and 5) Conducive environment for Persons with Disability Talent meeting Physical and Digital Accessibility standards 

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.

Experience: 4+ Years 

Location: India (Bangalore, Hyderabad/ Mumbai/ Gurugram)

Role Summary:

AuxoAI is seeking a Senior GenAI Data Engineer with strong fundamentals in data engineering and end-to-end solution design. In this role, you will design and develop production-grade pipelines, leverage GenAI tools (Copilot, Claude, Gemini) to boost development productivity, and define engineering best practices across complex data environments. This is a highly collaborative, cross-functional role — ideal for someone who thrives at the intersection of data engineering excellence and GenAI-powered innovation.

Responsibilities:

• Architect and develop end-to-end data pipelines — from ingestion to transformation to consumption

• Lead solutioning and integration for complex data workflows (batch and streaming)

• Use AI-assisted coding tools (e.g., GitHub Copilot, Claude, Gemini) to accelerate code development, refactoring, and debugging

• Implement robust data quality, testing, lineage, and governance frameworks

• Drive best practices across pipeline performance, reusability, and scalability

• Mentor junior engineers and contribute to capability building within the data team

Requirement:

• 4+ years of experience in data engineering, with expertise in:

      o End-to-end pipeline development (batch and streaming)

      o Data modeling (dimensional, Data Vault, OBT)

      o ETL/ELT design patterns, performance tuning, and optimization

      o SQL (Advanced) and Python (Advanced)

      o Apache Spark for large-scale data processing

• Proficiency using AI coding tools (e.g., Copilot, Claude, Gemini) to enhance productivity and code quality

• Strong understanding of data quality frameworks, unit testing, and CI/CD for data workflows

• Experience with Google Cloud Platform services: o BigQuery, Dataflow, Cloud Composer, Pub/Sub, Dataproc, Vertex AI

• Exposure to finance or sales data domains

• Familiarity with Databricks, Delta Lake, or Apache Iceberg

• GCP Professional Data Engineer certification is a plus

Role- Sr Senior Engineer 

Location -Hyderabad 

Shift -Night Shift starts from 8:30 PM IST 

About The Role

As a Senior Engineer on the team, you will own systems end to end across a high-volume, event-driven surface. You'll build the APIs and services behind key initiatives including:

- The driver comms platform — the rules engine, cohorting, and scheduling that reach drivers across SMS, push, and email

 - The onboarding funnel and applicant tracking layer, architected to support Veho's move to an in-house system over time

 - Live selling workflows that turn live offer and market-clearing data into well-timed, well-targeted driver outreach

You'll partner closely with Product, Design, Operations, and Data Science to ship tooling that scales with Veho's growth.

Responsibilities Include:

- Design, build, test, and deploy features across the driver-facing apps (driver mobile app, onboarding and registration surfaces), our GraphQL APIs, and the event-driven services behind them

 - Own a problem end to end: write the design doc your team works from, build it, roll it out behind a feature flag, and stay on it after launch until it is stable

 - Own the driver comms platform — the rules engine, cohorting, and scheduling that decide when to reach a driver over SMS, push, or email, and the delivery services behind it

 - Build the onboarding funnel and applicant tracking layer: registration and set-password flows, consent and eligibility gating, and the integrations that track where every applicant sits in the funnel

 - Build live selling workflows that consume live offer data and market-clearing signals to notify the right driver cohorts only when routes are actually claimable

 - Contribute to architectural decisions and technical design for complex, distributed systems, and architect today's comms and onboarding infrastructure so it supports the eventual in-house replacement of our third-party ATS rather than becoming throwaway work

 - Break a project into milestones your product, design, ops, and data partners can plan against

 - Write correctness-first code in an event-driven system where delivery is at-least-once and no driver may be texted twice about the same route — and where a send must never fire when there is no offer to claim

 - Improve reliability and observability in the services you own, with alerts that fire on real problems and stay quiet otherwise, so an on-call engineer is paged for a broken send pipeline and not for noise

 - Propose the engineering work your team should be doing, including the reliability, data-quality, and compliance work nobody is asking for

 - Use AI-native development workflows and tooling (Claude Code, Cursor, Copilot, and similar) as part of how you ship

 - Mentor the engineers around you, keep the team's code review bar high, and write down what you learn

What You Bring:

- 5–7+ years of experience building, testing, and deploying applications in high-traffic production environments

 - Depth in AWS serverless, including Lambda, a managed GraphQL layer such as AppSync, DynamoDB, EventBridge, and SQS

 - Experience with event-driven systems and the idempotency work that comes with at-least-once delivery — especially in a comms context where duplicate or misfired messages reach real people

 - Strong full-stack experience with TypeScript, Node.js, GraphQL, and React

 - Experience with DynamoDB single-table design

 - Experience integrating with third-party platforms and their webhooks, and keeping the data they produce in sync and trustworthy across services

 - At least one project owned through production rollout, including what broke afterward and who fixed it

 - Experience operating a service in production long enough to own its failure modes

 - Judgment about what a design costs in engineering time, dollars, and vendor commitment

 - A self-starter mindset with the ability to move quickly and ship iteratively, including on migrations, compliance obligations, and the manual steps nobody has automated yet

 - Enthusiasm for working closely with product, design, operations, data science, and support partners

-Tech Stack: AWS, TypeScript, Node.js, React, React Native, GraphQL, DynamoDB, serverless event-driven architecture; 

multi-channel comms (SMS, push, email); Firebase Auth; Statsig for experimentation; Redshift/Databricks-backed data pipelines

Preferred:

 - Experience with applicant tracking / recruiting funnels or other funnel-driven onboarding systems, and the drop-off analysis that improves them

 - Experience with experimentation and analytics infrastructure (Statsig, Fivetran, Redshift, Databricks) to measure and tune what you ship

 - Consent modeling and compliance obligations (e.g., driver terms-and-conditions and messaging consent) that span services