Sr. AI/ML Engineer

Role & Responsibilities

As a Senior GenAI Engineer you will own the AI layer of our product — building the features that make Zenskar intelligent. This is not a research role and not a prompt-engineering role. You will build production AI systems that enterprise clients depend on, which means reliability, observability, and rigorous evals matter as much as the AI capability itself. You own the full vertical — the model, the pipeline, and the UI.

• Build and own CS Copilot — a real-time assistant for customer success teams, spanning STT pipelines, live transcription, and LLM-powered suggestions
• Build LLM-powered document understanding features — extracting structured, reliable data from unstructured enterprise documents
• Own AI feature UIs end-to-end — you build the interface, not just the model integration layer
• Design and maintain an eval framework — define what 'working' means for each AI feature and catch regressions before users do
• Drive model selection and integration decisions — choosing the right provider and approach for each use case, managing latency and cost
• Own AI platform reliability — observability, fallback behaviour, and graceful degradation when models fail
• Work closely with product, customer success, and the full-stack engineer — AI features only matter if they are usable and trusted by real users

THE IMPACT YOU'LL MAKE-

• You will define what AI means at Zenskar — the features you ship will be the most visible and differentiated parts of the product
• CS Copilot, if done well, changes how enterprise customer success teams operate every single day — this is a high-stakes, high-visibility surface
• You will establish the engineering culture around AI reliability at Zenskar — evals, observability, and disciplined iteration
• Your work will directly accelerate enterprise deals — AI features are increasingly a buying criterion for our clients
• You will be the person who brings engineering rigour to a domain where most companies ship demos and call it a feature

Ideal Candidate

• Strong Senior GenAI / AI Backend Engineer Profiles
• Mandatory (Experience 1) – Must have 4+ years of total software development experience, with at least 2+ years working on AI/LLM-based features in production
• Mandatory (Experience 2) – Must have strong backend engineering experience using Python (FastAPI / Django preferred) and building production-grade systems
• Mandatory (Experience 3) – Must have hands-on experience building LLM-based applications, including OpenAI / Gemini / similar models in real projects
• Mandatory (Experience 4) – Must have experience with RAG (Retrieval Augmented Generation) including chunking, embeddings, and retrieval pipelines
• Mandatory (Experience 5) – Must have experience designing end-to-end AI pipelines, including chaining, tool usage, structured outputs, and handling failure cases
• Mandatory (Experience 6) – Must have experience building agentic AI systems (multi-step workflows, tool orchestration like LangGraph / CrewAI or custom agents)
• Mandatory (Experience 7) – Must have strong coding and system design skills, not just prompt engineering or experimentation
• Mandatory (Experience 8) – Must have experience shipping AI features in production, not just POCs or research projects
• Mandatory (Experience 9) – Must have experience working with APIs, backend services, and integrations
• Mandatory (Experience 10) – Must have understanding of AI system reliability, including latency, cost optimization, fallback handling, and basic eval thinking
• Mandatory (Company) – Product companies / startups, preferably Series A to Series D
• Mandatory (Note) - Candidate's overall experience should not be more than 7 Yrs
• Mandatory (Tech Stack) – Strong in Python + AI/LLM ecosystem, experience with modern AI tooling and frameworks
• Mandatory (Exclusion) – Reject profiles that are only Prompt Engineers, Data Scientists, or Frontend Engineers without strong backend + system building experience
• Preferred (Skill) – Experience with fine-tuning (LoRA / QLoRA) or open-source model deployment (vLLM / Ollama)
• Preferred (Frontend) – Basic ability to build or contribute to frontend (React or similar)
• Highly Preferred (Education) – Candidates from Tier-1 institutes (IITs, BITS, NITs, IIITs, top global universities)

Job Title: Graph Database Engineer (Neo4j / Knowledge Graph)

Experience: 4–8 Years (Preferred)

Key Responsibilities

• Design, develop, and optimize graph database solutions using GraphDB technologies.
• Build, maintain, and query graph data models for enterprise applications.
• Develop and manage Knowledge Graphs to support AI and data-driven use cases.
• Design graph schemas, relationships, and ontologies for efficient data representation.
• Collaborate with AI/ML, data engineering, and application development teams to integrate graph-based solutions.
• Optimize graph queries and ensure high performance, scalability, and reliability.

Required Skills

• Strong hands-on experience with Graph Databases.
• Neo4j experience is highly preferred.
• Proficiency in Cypher query language and graph data modeling.
• Good understanding of graph database architecture, indexing, and performance optimization.
• Experience with REST APIs and integrating graph databases with enterprise applications.
• Familiarity with Java, Python, or similar programming languages.

Preferred Skills

• Experience in building and managing Knowledge Graphs.
• Exposure to AI/ML, Generative AI, or Retrieval-Augmented Generation (RAG) solutions using graph databases.
• Knowledge of semantic technologies such as RDF, SPARQL, or OWL is an added advantage.
• Experience with cloud platforms (AWS, Azure, or GCP) is a plus.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
• Excellent analytical, problem-solving, and communication skills.

Nice to Have

• Experience with GraphRAG, LLM-based applications, or AI-powered knowledge management systems.
• Understanding of enterprise data integration and ontology design.

Responsibilities

• Developing new user-facing features using React.js
• Building reusable components and front-end libraries for future use
• Translating designs and wireframes into high quality code
• Optimizing components for maximum performance across a vast array of web-capable devices and browsers

Skills

• Strong proficiency in JavaScript, including DOM manipulation and the JavaScript object model
• Thorough understanding of React.js and its core principles
• Experience with popular React.js workflows (such as Flux or Redux)
• Knowledge of isomorphic React is a plus
• Familiarity with RESTful APIs
• Knowledge of modern authorization mechanisms, such as JSON Web Token
• Experience with common front-end development tools such as Babel, Webpack, NPM, etc.
• Ability to understand business requirements and translate them into technical requirements
• A knack for benchmarking and optimization
• Familiarity with code versioning tools such as Git, SVN, and Mercurial

The ideal candidate should be a proactive individual with strong communication skills and a team player.

Should have hands-on experience in the following:

• He or she should have experience of at least 2 - 4 years in Java development.
• Hands-on experience in designing and developing applications using Java EE platforms and at least 2 - 4 years of experience on the same.
• Should have excellent in-depth knowledge on core java, JSP, servlets, and beans
• Experience in multi-threaded server-side Java programming
• Working knowledge of web services.
• Working knowledge on hibernate and springs framework.
• Experience in writing SQL queries.
• Should have worked in an SDLC environment.
• Good communication skills.
• Experience in working effectively within a team

• Product Analytics: This is the first and most obvious role of the Product Analyst. At this capacity, the Product Analyst is responsible for the development and delivery of tangible consumer benefits through the product or service of the business.
• In addition, in this capacity, the Product Analyst is also responsible for measuring and monitoring the product or service’s performance as well as presenting product-related consumer, market, and competitive intelligence.
• Product Strategy: As a member of the Product team, the Product Analyst is responsible for the development and proposal of product strategies.
• Product Management Operations: The Product Analyst also has the obligation to respond in a timely manner to all requests and inquiries for product information or changes. He also performs the initial product analysis in order to assess the need for any requested changes as well as their potential impact.
• At this capacity, the Product Analyst also undertakes financial modeling on the products or services of the business as well as of the target markets in order to bring about an understanding of the relations between the product and the target market. This information is presented to the Marketing Manager and other stakeholders, when necessary.
• Additionally, the Product Analyst produces reports and makes recommendations to the Product Manager and Product Marketing Manager to be used as guidance in decision-making pertaining to the business’s new as well as existent products.
• Initiative: In this capacity, the Product Analyst ensures that there is a good flow of communication between the Product team and other teams. The Product Analyst ensures this by actively participating in team meetings and keeping everyone up to date.
• Pricing and Development: The Product Analyst has the responsibility to monitor the market, competitor activities, as well as any price movements and make recommendations that will be used in key decision making. In this function, the Product Analyst will normally liaise with other departments such as the credit/risk in the business in order to enhance and increase the efficiency of effecting price changes in accordance with market shifts.
• Customer/Market Intelligence: The Product Analyst has the obligation to drive consumer intelligence through the development of external and internal data sources that improve the business’s understanding of the product’s market, competitor activities, and consumer activities.
• In the performance of this role, the Product Analyst develops or adopts research tools, sources, and methods that further support and contribute to the business’s product.

• Candidate Must be well versed with latest SDK versions, XCode, Objective C, Swift, UIKit, Cocoa etc.
• Expertise in integrating web services (XML/ JSon etc.) with iPhone applications.
• An experience in using Maps API, GPS services for iPhone/ iOS apps is required.
• Experience with third-party libraries and APIs.
• Working knowledge of the general mobile orientation, architectures, trends, and emerging technologies.
• Experience working with iOS frameworks such as Core Data, Core Animation, Core Graphics and Core Text, Core Location.
• To take care of build and release process (Adhoc releases, Final release).
• Should have worked on cocoa touch, story board, core data, auto layout.
• Hands-on experience in Cloud APIs, push notifications, social media integration, and integration of analytics is an added advantage.
• Must have good analytical, debugging, App publishing and problem solving skills.
• Self-starter having the ability to independently acquire the knowledge required in succeeding his job.