Technical Project Manager

2 days ago

Mumbai, Maharashtra, India Straive Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Key Responsibilities: Project Management

  • Own the end-to-end delivery of Generative AI projects — from requirements gathering to deployment and adoption.
  • Collaborate with data scientists, ML engineers, prompt engineers, and product managers to design scalable AI-powered solutions.
  • Evaluate, select, and integrate LLM platforms and APIs (e.g., GPT-5, Claude, Gemini, Mistral, LLaMA) into enterprise applications.
  • Define and manage project plans, timelines, budgets, and resource allocations.
  • Oversee prompt engineering, model fine-tuning, and RAG (Retrieval-Augmented
  • Generation) implementations for production-grade use cases.
  • Ensure AI solutions meet security, compliance, and ethical AI standards, including data privacy and bias mitigation.
  • Drive performance monitoring and evaluation of deployed AI models, ensuring they meet agreed SLAs.
  • Liaise with business stakeholders to translate high-level goals into actionable technical requirements.
  • Create risk management and contingency plans specific to AI system deployment and scaling.
  • Stay up to date with Gen-AI trends, research breakthroughs, and tool advancements, and proactively bring innovative ideas to the table.

You will have the following qualifications:

  • Project Management Expertise: Strong track record managing technical projects in Agile/Scrum or hybrid delivery models.
  • Generative AI Implementation: Hands-on experience integrating and deploying solutions using GPT-4/5, Claude, Gemini, or equivalent LLMs.
  • Architecture Understanding: Familiarity with transformer-based architectures, embeddings, vector databases (Pinecone, Weaviate, FAISS), and API integrations.
  • Prompt Engineering Skills: Experience designing optimized prompts, context windows, and fine-tuned conversational flows.
  • RAG Pipelines: Understanding of retrieval-augmented generation for knowledge-base-enhanced LLM outputs.
  • Cloud & DevOps: Knowledge of AWS, Azure, or GCP AI/ML services; CI/CD pipelines for AI workloads.
  • Data Security & Compliance: Knowledge of enterprise security standards, GDPR, SOC 2, HIPAA (as relevant).
  • Stakeholder Communication: Exceptional ability to convey technical details to non-technical stakeholders.

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