JK Technosoft Ltd

Product Manager – AI/GenAI

Our AI platform that lets people ask questions of their enterprise data in natural language and get trustworthy answers. The hard part isn't the model — it's the fit between what the product can genuinely do and what customers actually need, over data that is never as clean as anyone hopes. We're hiring a Product Manager to own that fit: to do the detailed thinking on customer pain, competitive landscape, and where the technology is going, and to turn it into a sharp, defensible product proposition and roadmap. You'll work closely with the CTO (who currently carries this thinking) and become the person who owns the depth beneath it.

What you'll own

• Proposition & positioning. Take fuzzy capability and turn it into a clear, honest, defensible articulation of what Jiva is, who it's for, and why it wins. Kill the gap between what's sold and what's deliverable.

• Customer intelligence (within the current structure). Sales and Delivery own the customer relationship today; you build the customer picture through them —mining PoC post-mortems, win/loss, readiness audits, sales-call notes, and Delivery's ground truth. Extract real jobs-to-be-done, separate stated wants from underlying pain, and bring a synthesized customer voice into the room. Over time, earn a path to direct customer contact — but you'll start by getting more 

out of the signal the field teams already carry than anyone does today.

• Competitive & technology intelligence. Track the space — RAG, text-to-SQL, tabular/relational foundation models, agentic systems, the commercial players — and synthesize it into product direction. Know what's real and what's marketing.

• Requirements & roadmap. Translate the above into crisp requirements and a prioritized roadmap, in partnership with Engineering. Make the trade-offs explicit.

• Sales & Delivery enablement. Own the "what we can honestly promise" story so field teams stop overselling and start qualifying. You are the source of truth on capability boundaries.

Must-haves

• 5+ years in B2B / enterprise product management, ideally on data, analytics, AI/ML, or platform products.

• Demonstrated ability to frame a proposition — you can show us a product or feature where you turned raw capability into a positioning that won customers. Portfolio evidence, not a claim.

• Technical fluency in AI/data. You understand RAG, LLMs, text-to-SQL, and data quality well enough to judge feasibility vs. hype and to earn engineers' respect. You don't need to code; you need to reason.

• Customer discovery skill — and the resourcefulness to apply it 

indirectly. You've run structured discovery and can distinguish what customers say from what they need. Just as important here: you can extract sharp customer insight secondhand — through sales and delivery teams, deal histories, 

and product usage — because you won't have direct customer access on day one.

• Evidence-driven and structured. You validate before you evangelize. Strong written thinker — you can put a proposition on one page and defend it.

Nice-to-have

• Exposure to NL→SQL, semantic layers, knowledge graphs, or enterprise data governance.

• 0-to-1 or turnaround experience — comfort building the function, not just running it.

• Experience selling into or building for regulated / data-sensitive enterprises

Roles and Responsibilities:

• Design, develop, and maintain the end-to-end MLOps infrastructure from the ground up, leveraging open-source systems across the entire MLOps landscape.
• Creating pipelines for data ingestion, data transformation, building, testing, and deploying machine learning models, as well as monitoring and maintaining the performance of these models in production.
• Managing the MLOps stack, including version control systems, continuous integration and deployment tools, containerization, orchestration, and monitoring systems.
• Ensure that the MLOps stack is scalable, reliable, and secure.

Skills Required:

• 3-6 years of MLOps experience
• Preferably worked in the startup ecosystem

Primary Skills:

• Experience with E2E MLOps systems like ClearML, Kubeflow, MLFlow etc.
• Technical expertise in MLOps: Should have a deep understanding of the MLOps landscape and be able to leverage open-source systems to build scalable, reliable, and secure MLOps infrastructure.
• Programming skills: Proficient in at least one programming language, such as Python, and have experience with data science libraries, such as TensorFlow, PyTorch, or Scikit-learn.
• DevOps experience: Should have experience with DevOps tools and practices, such as Git, Docker, Kubernetes, and Jenkins.

Secondary Skills:

• Version Control Systems (VCS) tools like Git and Subversion
• Containerization technologies like Docker and Kubernetes
• Cloud Platforms like AWS, Azure, and Google Cloud Platform
• Data Preparation and Management tools like Apache Spark, Apache Hadoop, and SQL databases like PostgreSQL and MySQL
• Machine Learning Frameworks like TensorFlow, PyTorch, and Scikit-learn
• Monitoring and Logging tools like Prometheus, Grafana, and Elasticsearch
• Continuous Integration and Continuous Deployment (CI/CD) tools like Jenkins, GitLab CI, and CircleCI
• Explain ability and Interpretability tools like LIME and SHAP

Roles and Responsibilities:

·         Design and implement scalable web applications and platforms using technologies such as Typescript, NestJS, Angular, NodeJS, ExpressJS, TypeORM, and Postgres

·         Good understanding of web and REST API design patterns

·         Experience with AWS technologies such as EKS, ECS, ECR, Fargate, EC2, Lambda, ALB will be an added advantage

·         Hands-on experience with unit test frameworks like Jest

·         Good working knowledge of JIRA, Confluence, Git

·         Basic knowledge of Kubernetes and Terraform for infrastructure as code

·         Basic knowledge of Docker compose and Docker

·         Strong understanding of microservices architecture and ability to implement components independently

·         Proven track record of problem-solving skills

·         Excellent communication skills

Experience – 8 – 10 years

Location - NCR

Roles and Responsibilities:

System Analyst

The individual in this role will gather, document, and analyze client functional, transactional, and insurance business requirements across all insurance functions and third-party integrations. System Analyst will also work within a cross-functional project team to provide business analytical support and leadership from the business side.  The individual will play a highly visible, client-facing, and the consultative role and have the ability to offer system solutions to enhance client implementations and transform client workflow and business processes. Individual should be very good in mapping business functions / attributes with the Insurance rules and data.

Skills Required:

• A successful candidate in this role must:
• Good hands-on skills in Oracle, PL/SQL, TSQL
• Object oriented knowledge should be good
• Have Functional knowledge on P & C
• Overall Tech - 60% and Functional - 40%

Primary Skills:

• Good Data Mapping knowledge, RDBMS / SQL Knowledge

Secondary Skills:

• Oracle Big+

• Roles and Responsibilities:
  
  Hands-on experience on Angular, CSS, Scripting, NodeJs/express
  Experience in Responsive Web, Automation, CI/CD, Github, Microservices, Postgres (or any other RDBMS)
  Experience in AWS (SQS, SNS, Cognito)
  Implementing Observability/Monitoring.
  Strong experience in REST APIs