Machine Learning Lead at Meraki Labs · Bengaluru (Bangalore) · 8 - 12 years · ₹60L - ₹70L / yr · Raised funding · Posted 12 Dec 2025
Job Overview:
As a Technical Lead, you will be responsible for leading the design, development, and deployment of AI-powered Edtech solutions. You will mentor a team of engineers, collaborate with data scientists, and work closely with product managers to build scalable and efficient AI systems. The ideal candidate should have 8-10 years of experience in software development, machine learning, AI use case development and product creation along with strong expertise in cloud-based architectures.
Key Responsibilities:
AI Tutor & Simulation Intelligence
- Architect the AI intelligence layer that drives contextual tutoring, retrieval-based reasoning, and fact-grounded explanations.
- Build RAG (retrieval-augmented generation) pipelines and integrate verified academic datasets from textbooks and internal course notes.
- Connect the AI Tutor with the Simulation Lab, enabling dynamic feedback — the system should read experiment results, interpret them, and explain why outcomes occur.
- Ensure AI responses remain transparent, syllabus-aligned, and pedagogically accurate.
Platform & System Architecture
- Lead the development of a modular, full-stack platform unifying courses, explainers, AI chat, and simulation windows in a single environment.
- Design microservice architectures with API bridges across content systems, AI inference, user data, and analytics.
- Drive performance, scalability, and platform stability — every millisecond and every click should feel seamless.
Reliability, Security & Analytics
- Establish system observability and monitoring pipelines (usage, engagement, AI accuracy).
- Build frameworks for ethical AI, ensuring transparency, privacy, and student safety.
- Set up real-time learning analytics to measure comprehension and identify concept gaps.
Leadership & Collaboration
- Mentor and elevate engineers across backend, ML, and front-end teams.
- Collaborate with the academic and product teams to translate physics pedagogy into engineering precision.
- Evaluate and integrate emerging tools — multi-modal AI, agent frameworks, explainable AI — into the product roadmap.
Qualifications & Skills:
- 8–10 years of experience in software engineering, ML systems, or scalable AI product builds.
- Proven success leading cross-functional AI/ML and full-stack teams through 0→1 and scale-up phases.
- Expertise in cloud architecture (AWS/GCP/Azure) and containerization (Docker, Kubernetes).
- Experience designing microservices and API ecosystems for high-concurrency platforms.
- Strong knowledge of LLM fine-tuning, RAG pipelines, and vector databases (Pinecone, Weaviate, etc.).
- Demonstrated ability to work with educational data, content pipelines, and real-time systems.
Bonus Skills (Nice to Have):
- Experience with multi-modal AI models (text, image, audio, video).
- Knowledge of AI safety, ethical AI, and explain ability techniques.
- Prior work in AI-powered automation tools or AI-driven SaaS products.
Shubham Vishwakarma
Full Stack Developer - Averlon
About Meraki Labs
About
Company social profiles
Similar jobs (10)
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 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.
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
Key Responsibilities:
· Architectural Leadership: Design and lead the development of robust, scalable AI architectures, ensuring high performance, reliability, and security.
· Applied Mathematics & Statistics: Apply statistical analysis, numerical computation, and mathematical modeling to derive insights from large-scale data and optimize model performance.
· Deep Learning Development: Design, train, and deploy advanced Deep Learning (DL) models.
· Technical Mentorship: Mentor engineering teams on best practices for AI/ML, coding standards, and architectural design.
· Model Optimization: Optimize models for speed, efficiency, and accuracy using techniques like pruning, quantization, or GPU acceleration.
· Strategy & Innovation: Evaluate and select appropriate AI frameworks, tools, and platforms, staying abreast of cutting-edge research and industry trends.
Qualifications:
Required:
· Education: Master's or PhD in Computer Science, Applied Mathematics, Statistics, Physics, or a related quantitative field.
· Experience: 10+ years of experience in software development, with at least 3-5 years in a Applied Mathematics and Deep learning.
· AI/ML Expertise: Proven experience designing and deploying deep learning models in production using frameworks.
· Mathematics/Statistics: Strong proficiency in linear algebra, calculus, probability, and statistical methods.
· Programming Skills: Expert-level coding skills in Python (NumPy, Pandas, Scikit-learn) and experience with languages like Java or C++.
Key Competencies:
- Strategic mindset with deep operational awareness.
- Excellent communication and stakeholder management skills.
- Ability to simplify complex technical concepts for executive reporting.
- Strong leadership, people development, and cross-functional influencing skills.
Bias for action and a relentless focus on continuous improvement.
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 Company
The client is revolutionising the way businesses operate through cutting-edge technological solutions. Their focus is on developing intelligent agents and agentic workflows that automate processes and eliminate the need for human effort wherever possible. By leveraging
advanced AI and machine learning, they create systems that enhance productivity and drive efficiency.
Their expertise extends to the fintech, healthcare and medical technology sectors, where they develop innovative solutions that improve patient outcomes and streamline medical operations.
From medical devices to healthcare platforms, their work sits at the intersection of technology and medicine, pushing the boundaries of what's possible. The team is dedicated to continuous learning and growth, ensuring the team members are always at the forefront of the tech landscape.
About the Role
This is a senior, hands-on engineering role at the heart of our product team. You will be one of the most technical people in the room — setting the architecture for our real-time voice AI
agents and building the hardest parts of it yourself. From the systems that power live conversations to the interfaces our clients rely on, you will own how the product is engineered end to end.
We are looking for a genuine lead full-stack engineer with the depth to make architecture decisions that hold up as we scale, and the appetite to still be in the code every day. You should be as comfortable designing the backend services behind a live voice agent as you are shaping a clean interface on top of them — and comfortable being the person others turn to when something is hard.
You will work directly with the founder and product leadership on a fast-moving product, with real influence over technical direction. This is a role for someone who wants ownership at the level of "how the whole thing is built," not just individual features — and who raises the bar for
everyone around them.
What You'll Own
Set the technical direction
- Own the architecture of our core systems — the real-time voice agents, backend
- services, data and APIs — making the decisions that keep the product fast, reliable and scalable as it grows.
- Lead the hardest engineering problems and solve them personally.
- Establish engineering standards — code quality, review practices, testing and technical patterns that the team builds to.
- Drive technical strategy with the founder and product leadership — shaping the roadmap, flagging risk early, and turning product ambition into a sound technical plan.
Build the product end to end
- Design, build and ship features across the stack — backend services, APIs and front-ends — owning them from idea to production.
- Build the client-facing surfaces — dashboards, review tools and configuration interfaces that let our clients run and trust the product.
- Design and evolve the data models and APIs that hold up as we scale across clients.
Make it reliable and fast
- Own production quality — put the monitoring and alerting in place so issues are caught before clients feel them, and performance stays within target.
- Care about performance — find and fix bottlenecks across the stack.
- Build for correctness — put the testing and evaluation in place that keeps the product behaving predictably as it changes.
Lead through the team
- Mentor and grow engineers — through code review, pairing, and setting a technical example others learn from.
- Multiply the team's output — unblock others and lift the overall quality of the codebase.
- Take features from ambiguity to done — turn a rough product goal into a shipped, working capability with minimal hand-holding, and help others do the same.
What We're Looking For
- 8+ years of professional software engineering experience, with significant depth across backend and a track record of owning systems, not just features.
- Strong backend engineering, ideally in Python — building and scaling production services and APIs..
- Proven architecture and system-design ability — you have designed systems that scaled, and can reason clearly about trade-offs.
- Solid fundamentals across APIs, databases and cloud infrastructure.
- Experience building real-time and/or AI-powered products — or clear, demonstrable ability to lead in this area.
- A history of technical leadership — setting standards, mentoring engineers, and being trusted with the hardest problems — while remaining hands-on.
- Excellent communication and a genuine ownership mindset — someone who can be handed an ambiguous, high-stakes problem and be trusted to see it through.
Nice to Have
- Experience working with AI / large language models in production.
- Experience with voice or other real-time products.
- Exposure to healthcare, fintech, or other regulated / high-stakes domains.
- Experience as an early or senior engineer in a startup, where you set direction and wore many hats.
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
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
- Architecture - Design AI agents, RAG systems, integrations, and the scalable backend systems around them, for multiple client engagements.
- Technical scoping - Work directly with clients to turn a business problem into a system design, with clear trade-offs and clear reasons.
- Scale and reliability - Make sure what we build handles real load: data stores, queues, caching, horizontal scaling, and fault tolerance.
- Design reviews - Review designs and builds across engagements. Set the technical bar and hold it.
- Evaluation strategy - Define how we measure accuracy, safety, latency, and cost for the AI systems we ship.
- Guiding engineers - Raise the level of the engineers building with you, through reviews and direct pairing.
- Feedback to the platform - Feed what you learn across engagements back into our platform and internal tools.
What we are looking for
- Around 7 or more years of software engineering experience, including direct work with customers on design or delivery.
- Full-stack development experience with strength in backend technologies.
- Experience designing and building scalable applications. You understand how large-scale distributed systems work: data partitioning, queues, caching, horizontal scaling, and fault tolerance.
- At least 2 years of strong, hands-on AI experience with large language models in production.
- 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.
- Hands-on experience building retrieval-augmented generation (RAG) systems: chunking, embeddings, vector databases, retrieval, and reranking.
- Hands-on experience building AI agents.
- Strong programming skills in Python. Working knowledge of TypeScript or JavaScript.
- Experience with at least one cloud platform (AWS, Azure, or GCP).
- Clear communication. You can explain an architecture decision to an engineer and to a business leader, and defend it under questioning.
- High ownership and comfort with ambiguity. You can take an unclear problem and turn it into a design.
Nice to have
- Experience building evaluations to measure accuracy, safety, latency, and cost.
- Experience with observability and tracing tools such as LangSmith or Braintrust.
- Experience with on-premises or private cloud (VPC) deployments.
- Experience deploying AI systems in regulated industries such as insurance, banking, or the public sector.
- Experience with data engineering and pipelines.
- A history of side projects, open source contributions, or products you shipped end-to-end.
- Experience working at a consulting or professional services firm in a client-facing delivery role.
Stack and tools
- Languages: Python and TypeScript.
- Models: Claude and other frontier or open-source models, chosen to fit the customer.
- AI patterns: RAG, agents, prompt engineering, skills, and evaluations.
- Vector and retrieval: vector databases and retrieval pipelines.
- Cloud: AWS, Azure, or GCP, on public or private cloud.
- Integration: REST APIs and enterprise system connectors.
Job Description: Tech Lead – AI & Technology
Role Title: Tech Lead – AI & Technology
Location: Bangalore, India – Fully On-site
Experience: 5+ Years
Employment Type: Full-time
About the Role
We are looking for an experienced and hands-on Tech Lead to lead a small engineering team and drive the development of AI-powered applications, internal technology platforms, and modern IT solutions. The Tech Lead will be responsible for technical direction, architecture, development, code quality, team management, and end-to-end delivery of technology projects. The ideal candidate should have strong programming experience, particularly in Python and ReactJS, along with practical experience working with AI/ML technologies.
1. Technical Leadership & Team Management
- Lead and mentor a team of developers and technical team members.
- Own technical delivery across multiple projects and initiatives.
- Assign tasks, review progress, resolve technical blockers, and ensure timely delivery.
- Conduct code reviews and establish engineering best practices.
- Mentor team members and support their technical growth.
2. Software Development & Architecture
- Design and develop scalable, secure, and maintainable applications.
- Lead backend development using Python and frontend development using ReactJS.
- Define application architecture, technology choices, APIs, integrations, and development standards.
- Review technical designs and ensure high-quality implementation.
- Troubleshoot complex technical issues and drive effective solutions.
3. AI & Technology
- Lead the development and integration of AI-powered applications and solutions.
- Work with AI/ML models, APIs, LLMs, Generative AI, and related technologies.
- Evaluate emerging AI tools and technologies and identify opportunities for practical implementation.
- Collaborate with product and business teams to translate requirements into AI-enabled technology solutions.
4. Project Delivery
- Own the complete technology lifecycle from requirements and architecture to development, testing, deployment, and maintenance.
- Plan sprints, estimate development efforts, and track technical milestones.
- Work closely with cross-functional stakeholders to understand requirements and deliver solutions.
- Ensure projects meet timelines, quality standards, security requirements, and performance expectations.
5. Engineering Quality & Infrastructure
- Establish standards for coding, testing, documentation, version control, and deployment.
- Ensure applications are scalable, reliable, and secure. l Collaborate on cloud infrastructure, APIs, databases, CI/CD, and deployment processes.
- Identify opportunities to improve system performance and engineering efficiency.
Technical Skills – Must Have
- 5+ years of software development experience.
- Strong hands-on experience with Python.
- Strong experience with ReactJS / React.
- Experience leading or managing technical team members.
- Strong understanding of AI/ML and Generative AI technologies.
- Experience with APIs, databases, Git, and software development lifecycle.
- Strong understanding of application architecture and system design.
- Experience building and deploying production-grade applications.
Technical Skills – Good to Have
- Experience with LLMs, RAG, AI agents, or Generative AI applications.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Experience with Docker, CI/CD, and DevOps practices.
- Experience integrating third-party AI APIs and services.
- Experience working in startups or fast-paced technology environments.
What We Are Looking For
- Strong technical ownership and problem-solving ability.
- Ability to balance hands-on coding with team leadership.
- Excellent communication and stakeholder management skills.
- Ability to mentor developers and drive accountability within the team
- Strong interest in AI and emerging technologies.
- A proactive, ownership-driven approach with the ability to work in a fast-paced environment.
Why Join Us?
- Work on AI-powered technology with meaningful social impact.
- Lead a small, high-ownership technology team.
- Work across AI, software engineering, and modern IT infrastructure.
- Opportunity to shape technology architecture and engineering practices from the ground up.
- Collaborative and fast-moving environment with significant technical ownership.
What We Are Looking For
CLOUDSUFI is seeking a senior, hands-on AI Platform Architect to design and build production-grade platforms for generative AI, agentic systems, data-intensive applications, and analytical workflows. This is a builder-architect role. The successful candidate will define architecture, make technology decisions, develop reference implementations, review critical code and designs, and guide engineering teams from prototypes to secure, scalable production systems. We are looking for a builder-architect with strong engineering judgement and practical delivery experience. The right candidate can define platform direction, evaluate trade-offs, validate ideas through implementation, and guide systems into production. They should be equally comfortable discussing distributed architecture, reviewing code, diagnosing workflow failures, designing evaluation systems, and mentoring engineering teams.
Key Responsibilities-
AI and Agentic Platform Architecture
• Design platforms for single-agent and multi-agent systems supporting planning, reasoning, tool use, memory, delegation, validation, and human approval.
• Define orchestration patterns for deterministic, dynamic, event-driven, and long-running AI workflows.
• Establish clear boundaries between LLM reasoning, application logic, quantitative computation, rules, and human decision-making.
• Evaluate and adopt agent frameworks, model providers, tools, and orchestration technologies based on reliability, flexibility, performance, and cost. Knowledge and Data Systems
• Architect RAG pipelines, document-processing systems, vector search, hybrid retrieval, knowledge graphs, and semantic data layers.
• Integrate structured and unstructured enterprise data from APIs, databases, files, streams, and external platforms.
• Design reusable workflows for research, data collection, transformation, analysis, modelling, validation, and reporting.
• Establish data lineage, provenance, metadata, access controls, freshness, and quality standards. Evaluation, Observability and Governance
• Build evaluation frameworks for accuracy, relevance, groundedness, task completion, tool use, safety, latency, and cost.
• Enable systematic experimentation across models, prompts, agents, tools, retrieval strategies, and orchestration patterns.
• Implement versioning and lifecycle management for prompts, agents, workflows, datasets, knowledge bases, evaluations, and model configurations.
• Establish tracing, monitoring, auditability, guardrails, approval workflows, and production quality diagnostics.
Cloud and Platform Engineering
• Define cloud-native architectures using microservices, APIs, event-driven systems, queues, schedulers, and distributed processing.
• Lead Kubernetes-based deployment, containerisation, CI/CD, Infrastructure as Code, environment management, and release automation.
• Design for horizontal scalability, fault tolerance, resilience, security, data privacy, and high availability.
• Optimise model usage, infrastructure, storage, retrieval, and compute for performance, latency, and cost.
Technical Leadership
• Translate product and business requirements into clear technical designs and implementation plans.
• Build prototypes and reference implementations for high-risk or foundational platform capabilities.
• Review architecture, code, interfaces, data models, infrastructure, and operational readiness.
• Define engineering standards and reusable patterns across AI, backend, data, and platform teams.
• Mentor senior engineers and support teams in resolving complex technical and production issues.
Required Skills and Experience
• 10+ years of experience in software architecture, platform engineering, distributed systems, data platforms, or AI systems.
• Strong hands-on experience designing and building production-grade AI or data-intensive platforms.
• Deep understanding of LLM applications, tool calling, structured outputs, RAG, embeddings, memory, and agent orchestration.
• Strong experience with cloud platforms, Kubernetes, containers, microservices, APIs, event driven architecture, CI/CD, and Infrastructure as Code.
• Experience with relational, document, graph, vector, and distributed data systems.
• Practical experience implementing AI evaluation, experimentation, tracing, monitoring, guardrails, and lifecycle management.
• Strong understanding of security, identity, access control, secrets management, data protection, and production reliability.
• Ability to move effectively between architecture, code, infrastructure, debugging, and technical delivery.
Good to Have
• Experience building enterprise AI copilots, autonomous workflows, research platforms, or analytical systems.
• Experience with knowledge graphs, hybrid search, model gateways, tool gateways, or agent marketplaces.
• Familiarity with LLMOps, MLOps, model serving, feature stores, model registries, and distributed compute.
• Experience supporting real-time and batch data processing at scale.
• Experience comparing and operating multiple commercial and open-source models.
• Prior experience in consulting, client-facing architecture, or complex enterprise platform delivery.
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon