▷ [Urgent Search] Technical Project Manager

2 weeks ago

Mumbai India Straive Full time

Job Description

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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