NodeJS Architect

Location: Hyderabad, India. Based at the KnackLabs headquarters, with occasional travel to client locations for workshops and reviews. This role does not involve extended onsite deployments.

About the Role

You will work as an AI Architect who designs the systems behind our client engagements: AI agents, RAG systems, automation platforms, and the conventional backend systems around them.

This is a hands-on design role, not a slideware role. You will scope architectures with clients, make the hard technical decisions, defend them in review, and stay accountable for how the systems perform in production.

You will work directly with clients. Everyone at KnackLabs does. You will sit in design discussions with client engineering teams, present architecture decisions to technical and business stakeholders, and answer for the choices you make.

A full KnackLabs engineering team in Hyderabad builds with you. You own the technical design and the quality of what ships.

What you'll own

1. Architecture - Design AI agents, RAG systems, integrations, and the scalable backend systems around them, for multiple client engagements.
2. Technical scoping - Work directly with clients to turn a business problem into a system design, with clear trade-offs and clear reasons.
3. Scale and reliability - Make sure what we build handles real load: data stores, queues, caching, horizontal scaling, and fault tolerance.
4. Design reviews - Review designs and builds across engagements. Set the technical bar and hold it.
5. Evaluation strategy - Define how we measure accuracy, safety, latency, and cost for the AI systems we ship.
6. Guiding engineers - Raise the level of the engineers building with you, through reviews and direct pairing.
7. Feedback to the platform - Feed what you learn across engagements back into our platform and internal tools.

What we are looking for

1. Around 7 or more years of software engineering experience, including direct work with customers on design or delivery.
2. Full-stack development experience with strength in backend technologies.
3. Experience designing and building scalable applications. You understand how large-scale distributed systems work: data partitioning, queues, caching, horizontal scaling, and fault tolerance.
4. At least 2 years of strong, hands-on AI experience with large language models in production.
5. You build with AI coding tools like Claude Code or Codex as your default way of working. You understand Claude Skills, have written skills yourself, use them actively, and have contributed to them.
6. Hands-on experience building retrieval-augmented generation (RAG) systems: chunking, embeddings, vector databases, retrieval, and reranking.
7. Hands-on experience building AI agents.
8. Strong programming skills in Python. Working knowledge of TypeScript or JavaScript.
9. Experience with at least one cloud platform (AWS, Azure, or GCP).
10. Clear communication. You can explain an architecture decision to an engineer and to a business leader, and defend it under questioning.
11. High ownership and comfort with ambiguity. You can take an unclear problem and turn it into a design.

Nice to have

1. Experience building evaluations to measure accuracy, safety, latency, and cost.
2. Experience with observability and tracing tools such as LangSmith or Braintrust.
3. Experience with on-premises or private cloud (VPC) deployments.
4. Experience deploying AI systems in regulated industries such as insurance, banking, or the public sector.
5. Experience with data engineering and pipelines.
6. A history of side projects, open source contributions, or products you shipped end-to-end.
7. Experience working at a consulting or professional services firm in a client-facing delivery role.

Stack and tools

1. Languages: Python and TypeScript.
2. Models: Claude and other frontier or open-source models, chosen to fit the customer.
3. AI patterns: RAG, agents, prompt engineering, skills, and evaluations.
4. Vector and retrieval: vector databases and retrieval pipelines.
5. Cloud: AWS, Azure, or GCP, on public or private cloud.
6. Integration: REST APIs and enterprise system connectors.

Build AI where the work actually happens.

Celeco works inside real businesses to understand critical workflows, ship production AI systems and stay through adoption.

We are hiring our first Intelligence Architect (Forward-Deployed AI Engineer).

⌁

Full-time · Remote-first · Optional hybrid in Bengaluru

At least one year of professional engineering experience. Customer travel when the work requires it.

The role

An Intelligence Architect enters a customer environment with an unfinished question and leaves behind a working, measurable system.

This is a hands-on engineering role at the boundary of product, operations and customer delivery. You will learn the domain, inspect the existing systems and data, decide what should be built, and write the code that puts it into production.

What you will own

• Interview and shadow the people doing the work, then map the real workflow, including hand-offs, exceptions and workarounds.
• Understand the customer's application stack, APIs, data, identity model, security constraints and deployment environment.
• Turn business goals into a technical scope, system design, delivery plan and measures of success.
• Build across the stack: AI workflows, data pipelines, integrations, backend services and the interfaces people use.
• Choose the simplest reliable approach. The answer may combine agents, retrieval, rules and conventional software.
• Create evals from representative cases, define quality and failure metrics, inspect traces, red-team the system and set launch thresholds.
• Make practical trade-offs across accuracy, latency, cost, privacy, security and speed.
• Take prototypes into production with tests, monitoring, access controls, documentation and a plan for failure and recovery.
• Work beside customer teams during rollout and improve the system until it becomes part of the workflow.
• Turn what works into reusable components, evaluation sets and playbooks for future Celeco deployments.

You will probably thrive here if

• You have at least one year of professional software or product engineering experience.
• You have shipped a real system used by other people and can explain what you owned, what broke and what you changed.
• You are strong in Python or TypeScript and comfortable moving across unfamiliar codebases, APIs, databases and cloud services.
• You have built with language or multimodal models and understand prompting, structured outputs, retrieval, tool use and model failure modes.
• You use Cursor, Codex, Claude Code or similar tools as part of your engineering workflow, while still reviewing, testing and understanding the code you ship.
• You can create an evaluation set, choose useful quality metrics and improve a system through error analysis instead of prompt guesswork.
• You can speak with an operator, an engineering team and a senior leader without losing the thread of the problem.
• You work well with incomplete requirements, write clearly and surface risks early.
• You care about whether people use what you build and whether it changes a business outcome.
• You can commit full-time and travel to customer sites when discovery or rollout is better done in person.

Experience with cloud deployment, containers, CI/CD, observability, enterprise integrations, authentication or security is useful. We do not expect one person to arrive knowing every framework, cloud or industry.

What you will get

• Direct ownership of live customer problems from discovery through production.
• Close collaboration with Celeco's founders and customer leadership teams.
• Exposure to different industries, operating models and technical environments.
• The freedom to choose the technical approach and the responsibility to prove that it works.
• A role in defining Celeco's engineering methods, reusable systems and technical culture while the company is early.
• A remote-first setup, with the option to work together in Bengaluru.

If the work sounds like you but your background is unconventional, apply. We care more about what you have built, how you think and how quickly you learn than pedigree.

Technical Lead – Embedded Software Application Projects

link: https://www.ziliconcloud.com/careers

ZILICONCLOUD PRIVATE LIMITED is looking for an experienced Technical Lead with 5–8 years of industry experience in Embedded Systems, IoT, AI, Cloud, and Software Engineering.

The candidate will lead Embedded, IoT, Edge AI, and Cloud projects, define system architecture, convert requirements into technical tasks, and ensure successful project execution and delivery.

Key Responsibilities

• Design modular system architectures for Embedded, IoT, Edge AI, Cloud, REST APIs, and dashboards.
• Convert requirements into clear tasks, milestones, and deliverables.
• Track project progress, manage technical risks, and ensure on-time delivery.
• Guide engineers on coding standards, Git, testing, debugging, and documentation.
• Troubleshoot issues across hardware, firmware, IoT, cloud, backend, and UI.
• Support system integration, testing, debugging, and performance improvement.
• Review technical designs, code, and test results.
• Lead prototype development, integration, technical reviews, and demonstrations.
• Mentor young engineers and explain complex technical concepts in a simple and practical way.
• 
  

Required Skills

C/C++, Python, JavaScript/TypeScript, Linux, FreeRTOS, Microcontrollers, REST APIs, MQTT, Git, Embedded Software, IoT, and system debugging.

Preferred: AWS IoT, Microsoft Azure, ThingsBoard, OpenCV, TensorFlow Lite (TFLite), React, Flutter, or FastAPI.

Education

B.E./B.Tech/M.E./M.Tech in ECE, CSE, Embedded Systems, Mechatronics, or a related field.

📍 Location: East Tambaram, Chennai, Tamil Nadu

💼 Experience: 5–8 Years

🕒 Employment Type: Full-Time

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

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.

About the Company

As the world moves toward AI-native applications, one element matters more than anything: data.

We are building a platform that helps organizations unlock the value hidden within customer feedback. By centralizing data from multiple sources—including CRM platforms, support systems, collaboration tools, surveys, community forums, and customer conversations—into a unified intelligence layer, we enable teams to understand customer needs and make better product decisions.

Built on top of this foundation is an AI-powered platform that allows teams to query, monitor, and act on customer intelligence directly within their workflows. Our customers include some of the fastest-growing product-led technology companies as well as large global enterprises.

Backed by leading global venture capital firms, our engineering culture is AI-native from the ground up. Agents, LLMs, and applied machine learning are not side projects—they are central to how we build products. We operate at the cutting edge of agentic systems and continuously push the boundaries of what modern AI applications can achieve.

What You Will Do

• Convert product direction into phased technical plans, including estimates, milestones, dependencies, and risk assessments.
• Make thoughtful trade-offs across correctness, latency, user experience, AI/model behavior, reliability, cost, and delivery speed.
• Define clear ownership boundaries across frontend applications, BFF layers, backend services, agent workflows, ML platforms, and data contracts.
• Review ERDs, PRDs, design documents, and implementation plans to identify gaps before they become execution challenges.
• Drive planning and execution for complex initiatives while empowering area leads and senior engineers to maintain ownership.
• Partner closely with Product, Design, Engineering, and GTM teams to turn ambiguous problem statements into executable solutions.
• Influence technical direction through strong engineering judgment, architectural leadership, and hands-on involvement.
• Mentor senior engineers and contribute to engineering excellence through reviews, incident analysis, and proactive risk management.

What It Takes

• 5+ years of experience as a Senior Engineer, Technical Lead, or equivalent role.
• Demonstrated experience owning architecture and execution for large-scale product or platform initiatives spanning multiple teams.
• Strong foundation in distributed systems and modern software architecture.
• Exposure to agentic AI systems, machine learning engineering, MLOps platforms, and frontend/BFF architectures.
• Ability to own end-to-end product and technical problems rather than specializing exclusively in a single layer of the stack.
• Proven track record of converting ambiguity into actionable engineering plans.
• Excellent written communication skills, including design documentation, architectural reviews, trade-off analyses, and RCA documentation.
• Ability to challenge requirements constructively and collaborate effectively across Product, Design, Engineering, and GTM functions.
• High ownership mindset, attention to detail, and a low-ego, collaborative approach.

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.

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.

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.

We’re on hunt for AI Architect

Responsibilities:

• 10–15+ years overall experience, with recent hands-on AI/GenAI architecture ownership.
• Must have architected enterprise AI platforms/solutions end-to-end, not just individual ML models or PoCs.
• Strong GenAI/LLM production experience: RAG, embeddings, vector DBs, hybrid search, reranking, evaluation, guardrails.
• Strong Agentic AI understanding: agents, tool calling, workflows, orchestration, human-in-the-loop.
• Experience taking AI solutions from architecture → production → scale, ideally across multiple business teams/use cases.
• Strong cloud architecture — Azure/AWS preferred; hybrid/on-prem experience is a plus.
• Must understand enterprise security, governance, Responsible AI, observability and LLMOps/MLOps.
• Should be able to articulate build-vs-buy, MVP-vs-target architecture, cost/performance/security tradeoffs.
• Strong stakeholder-facing / consulting ability — can work with business leaders, engineering, security and data teams and influence without authority.

There is scope to move to the US for this role if you are aligned for the same, else this will be a WFO role from Hyderabad location