Project Manager – Generative AI Specialist

AI Project Manager

About Techjays

At Techjays, we are driving the future of artificial intelligence with a bold mission to empower businesses worldwide by helping them build AI solutions that transform industries. As an established leader in the AI space, we combine deep expertise with a collaborative, agile approach to deliver impactful technology that drives meaningful change. Our global team consists of professionals from leading companies such as Google, Akamai, NetApp, ADP, and Cognizant.

Role Overview

We are seeking a seasoned Project Manager to oversee the successful delivery of complex AI-driven projects. You will be responsible for bridging organizational goals with cross-functional execution, ensuring that our technical teams deliver high-quality solutions on schedule and within budget.

Key Recruitment Details

• Experience Required: 8 + Years (Minimum 6+ years in end-to-end project management)
• Work Location: Coimbatore / Hybrid
• Target Joining Date: (ASAP / Within 30 days)

Must-Have Qualifications

• Proven Execution: 6+ years of experience managing the complete lifecycle of enterprise-grade software projects.
• Agile Expertise: Advanced proficiency in Agile/Scrum methodologies, with a track record of facilitating sprint planning, stand-ups, and retrospectives.
• Technical Proficiency: Mastery of project management tools including Jira, MS Project, or Trello.
• Strategic Planning: Demonstrated experience in resource allocation, risk mitigation, and contingency planning.
• AI Enthusiasm: Experience leveraging AI tools in project management or a demonstrated passion for adopting AI technologies to optimize workflows.
• Stakeholder Management: Exceptional communication skills for managing both internal cross-functional teams and external client relationships.

Roles & Responsibilities

• Project Governance: Plan, execute, and monitor projects to ensure alignment with client expectations and organizational benchmarks.
• Team Leadership: Facilitate high-performing Agile environments, fostering a culture of collaboration, innovation, and technical ownership.
• Risk & Budget Management: Identify potential bottlenecks early, implement mitigation strategies, and manage project budgets to ensure optimal resource utilization.
• Reporting & Transparency: Track project progress using modern metrics, preparing detailed reports and presentations for senior management.
• Continuous Improvement: Analyze project outcomes to implement best practices and drive operational discipline across the engineering organization.
• Mentorship: Elevate team members through active support and guidance, ensuring professional growth within the team.

Success Milestones

Timeline

Expectations

First 30 Days

Audit active project pipelines, establish stakeholder relationships, and assume management of ongoing sprint cycles.

First 60 Days

Optimize resource allocation workflows, streamline cross-team communication, and implement improved risk-tracking mechanisms.

First 90 Days

Achieve >85% sprint commitment completion rate and stabilize project delivery predictability across assigned teams.

What Techjays Offers

• Competitive Compensation: Best-in-class packages structured to reflect experience and impact.
• Health & Wellness: Medical insurance covering self and family up to ₹4 lakhs per person.
• Flexibility: A trust-based time-off policy and a flexible hybrid work model.
• Environment: A casual work culture with a diverse, multicultural team that respects ideas regardless of designation.
• Growth: Meaningful professional development in an innovation-driven culture.

AI Developer  

Primary Skill-set (Must have) 

• Generative AI Expertise: 2-3 years of experience in designing and implementing generative AI solutions, including knowledge of various generative and autoregressive models. Ability to apply generative AI techniques to diverse use cases such as image generation, text generation, and creative content synthesis. 

• 2 years of experience in prompt engineering, fine tuning, agentic framework, GenAI SDK’s 

• 1-2 years of experience in Agentic AI frameworks like Autogen, Lanngraph, MS Agent SDK, A2A, MCP, A2P, memory concepts, multi agent orchestration 

• 7+ years of experience in Python 

• 5+ years of experience in software development 

• Azure Proficiency: 3-5 years of experience with Azure cloud services relevant to AI, including Azure Machine Learning, Azure Cognitive Services, Azure Databricks, and Azure Kubernetes Service (AKS). 2+ years of experience in Azure's capabilities to architect end-to-end AI solutions and optimize performance. 

• Architecture Design: 3-5 years of skills with the ability to design scalable, reliable, and cost-effective architectures for AI solutions. Proficiency in designing distributed systems, microservices architectures, and containerized solutions using technologies such as Docker and Kubernetes. 

Secondary Skills (Good to have) 

• Security and Compliance: Understanding of security principles and best practices in AI development, with the ability to implement security controls, encryption mechanisms, and access management policies to protect AI models and sensitive data. 

• Integration and Deployment: Proficiency in implementing CI/CD pipelines, automation scripts, and infrastructure as code (IaC) using tools such as Azure DevOps, Terraform, or Ansible. Experience in containerization and orchestration of AI workloads using Docker and Kubernetes. 

• Software Development: Strong programming skills in languages such as Python, with experience in developing AI applications, RESTful APIs, and microservices architectures. Familiarity with software development methodologies such as Agile or Scrum. 

• Communication and Presentation: Excellent communication skills with the ability to convey complex technical concepts to non-technical stakeholders. Experience in preparing and delivering technical presentations, architecture diagrams, and documentation to communicate architectural decisions and design rationale effectively. 

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.

Roles & Responsibilities

Product Strategy & Discovery

• Identify customer, business, and market opportunities through stakeholder engagement, customer research, discovery workshops, and data analysis.
• Define product vision, roadmap, value proposition, success metrics, and prioritization aligned with business objectives.
• Translate business and customer needs into product requirements, user stories, PRDs, and acceptance criteria.
• Own and continuously prioritize the product backlog based on business value, feasibility, dependencies, risks, and strategic priorities.

AI & Digital Innovation

• Identify and evaluate opportunities to leverage Generative AI, automation, and emerging technologies across products and business processes.
• Define AI-focused use cases, business cases, success metrics, user journeys, and MVP/PoC strategies.
• Collaborate with AI/ML, data, architecture, and engineering teams to convert AI opportunities into scalable product solutions.
• Drive adoption of AI across the product lifecycle and SDLC, including discovery, requirements management, development, testing, analytics, documentation, and support.
• Contribute to enterprise-wide AI initiatives and help scale successful AI PoCs into production-ready solutions.

Presales, Consulting & Solutioning

• Lead or contribute to RFP responses, proposals, client discovery sessions, workshops, and solution presentations.
• Understand client challenges and translate them into digital transformation, modernization, and AI-driven product opportunities.
• Develop solution concepts, use cases, product capabilities, roadmaps, value propositions, and implementation strategies.
• Partner with engineering, UX, architecture, delivery, and commercial teams to define scope, estimates, assumptions, dependencies, risks, and solution feasibility.
• Support client engagements and identify opportunities for account growth through product enhancements, modernization initiatives, and AI adoption.

Product Delivery & Governance

• Partner with UX, engineering, QA, architecture, and delivery teams to ensure successful product execution and delivery.
• Facilitate sprint planning, backlog refinement, UAT/SIT activities, release planning, production validation, and defect prioritization.
• Monitor product KPIs, delivery metrics, adoption, business outcomes, risks, and dependencies.
• Drive stakeholder alignment and continuous improvement throughout the product lifecycle.
• Mentor and guide Product Managers and product team members to strengthen product thinking, decision-making, stakeholder management, and delivery excellence.

Customer & Business Outcomes

• Leverage customer feedback, product analytics, experimentation, and market insights to drive continuous product improvement.
• Lead adoption and successful rollout of new capabilities through effective stakeholder engagement, communication, and change management.
• Ensure products and solutions deliver measurable customer, business, and operational outcomes.

Core Competencies

• Product strategy, discovery, roadmap planning, prioritization, and backlog management.
• Generative AI, AI product thinking, AI use-case identification, and digital innovation.
• Presales, consulting, solutioning, RFP response management, and client engagement.
• Strong business acumen with the ability to connect technology initiatives to business outcomes.
• Excellent communication, presentation, facilitation, and stakeholder management skills.
• Strong understanding of Agile/Scrum methodologies and end-to-end product delivery.
• Ability to collaborate effectively with engineering, architecture, UX, QA, data, and AI/ML teams.
• Strong analytical, problem-solving, and decision-making capabilities.
• Ability to manage ambiguity, multiple workstreams, and senior client stakeholders.

Qualifications

• B.E./B.Tech in Computer Science, Information Technology, Engineering, or an equivalent discipline.
• MBA or certifications in Product Management, Business Analysis, or related fields preferred.
• 10+ years of experience in Product Management, Product Ownership, or Business Analysis.
• Experience working in Agile/Scrum environments with cross-functional technology teams.
• CSPO, PSPO, CBAP, or CCBA certifications are desirable.

Location - India (Remote)

Bachelor’s degree in Engineering, Computer Science, or a related discipline

• 8+ years of experience in project or programme management

• 3+ years of experience delivering AI, Machine Learning, Data, or Analytics programmes

• PMP, Agile, Scrum, or equivalent certification preferred

Immediate Joiner - 15 days Notice period

• Primary Skillsets: Python, Generative AI, Agentic AI, LLM, experience with designing and developing production grade AI solutions, AWS/Azure/GCP, LLMOps, Data Engineering (Databricks/Snowflake), Regulated GenAI, Data and Decisions, and Agentic Systems.

• Preferred: Pharma or life sciences experience, especially in regulated (GxP) environments, experience setting up a team or practice from scratch.

Looking for an Architect with strong experience in AI and Data Engineering, preferably with hands-on experience in Generative AI (GenAI). Candidates with experience in any cloud platform (AWS, Azure, or GCP) will be considered, 

• Primary Skillsets: Python, Generative AI, Agentic AI, LLM, experience with designing and developing production grade AI solutions, AWS/Azure/GCP, LLMOps, Data Engineering (Databricks/Snowflake), Regulated GenAI, Data and Decisions, and Agentic Systems.
• Preferred: Pharma or life sciences experience, especially in regulated (GxP) environments, experience setting up a team or practice from scratch.
• Only immediate joiners are considered.

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

About the Role

We are looking for an AI/ML Engineer with 4+ years of Strong hands-on experience building and deploying production-grade AI systems. The ideal candidate should have strong expertise in Computer Vision, Generative AI, RAG pipelines, Voice AI, and LLM-powered applications, with experience delivering scalable, production-ready solutions across enterprise, healthcare, or SaaS environments

Key Responsibilities

• Design, develop, and deploy production-ready AI/ML and Generative AI applications, Computer Vision solutions.
• Build and optimize LLM-powered applications for real-world business use cases.
• Develop and maintain RAG (Retrieval-Augmented Generation) pipelines using vector databases and embedding models.
• Build Voice AI solutions including speech-to-text (STT), text-to-speech (TTS), conversational AI, and voice-enabled assistants.
• Create and optimize prompt engineering strategies to improve LLM output quality, consistency, and reliability.
• Work with open-source LLMs for inference, fine-tuning, evaluation, and deployment.
• Implement model monitoring, evaluation, guardrails, and performance optimization.
• Collaborate with DevOps and cloud teams for scalable deployments.
• Optimize AI systems for latency, cost, scalability, and production performance.
• Integrate AI services through APIs and enterprise applications.

Required Skills & Experience

• 4+ years of experience in AI/ML engineering and production deployments.
• Strong experience in Python and AI/ML development.
• Hands-on experience with Generative AI and LLM applications.
• Strong hands-on experience in Computer Vision using Python and frameworks such as OpenCV, PyTorch, and TensorFlow.
• Experience with Computer Vision tasks such as object detection, image classification, image segmentation, and feature extraction.
• Familiarity with models and libraries such as YOLO, Detectron2, MMDetection, and torchvision.
• Experience with image preprocessing, data augmentation, model training, evaluation, and inference optimization.
• Exposure to OCR technologies such as Tesseract or EasyOCR and vision-based deep learning models is an advantage.
• Experience building RAG pipelines using:
• Vector Databases: Pinecone, Weaviate, FAISS, ChromaDB, Milvus
• Embeddings and retrieval optimization
• Experience with Prompt Engineering techniques for LLM optimization.
• Experience with Open Source LLMs such as:
• Llama, Mistral, Falcon, Gemma, DeepSeek, Qwen
• Experience with Voice AI technologies:
• Speech-to-Text (Whisper, Deepgram, Google STT)
• Text-to-Speech (ElevenLabs, Azure Speech, Amazon Polly)
• Conversational Voice Agents
• Experience using frameworks/tools:
• LangChain, LangGraph, LlamaIndex, Hugging Face
• Understanding of fine-tuning, model evaluation, inference optimization, and AI observability.
• Experience deploying applications using:
• Docker, Kubernetes, CI/CD
• AWS / Azure / GCP

Preferred Qualifications

• Experience delivering AI solutions for Healthcare, Enterprise, or SaaS platforms.
• Exposure to MLOps practices and model lifecycle management.
• Understanding of AI governance, security, and responsible AI practices.
• Experience integrating AI with APIs and production services.

Nice to Have

• Knowledge of agentic AI workflows and orchestration.
• Experience with monitoring and evaluation frameworks.
• Exposure to multimodal AI applications

Education Qualifications

• B.Tech / M.Tech in CSE / IT / AI&ML only from good college.