AI-Technical Project Manager (Speech& LLM team)

Gnani Innovations Private Limited.; Hinoba-an; On-site; PHP 595,000 - 1,058,000; Full time

Job summary

Gnani.ai is seeking an AI Project Manager to lead Speech AI & LLM engineering delivery in our Bangalore-based team. You will coordinate planning, execution, and releases across ASR, TTS, and LLM workstreams, bridging Speech R&D, Product, and Platform Engineering to meet customer requirements.

You will own sprint planning, backlog health, roadmap tracking, and cross‑functional collaboration, ensuring timely releases and data-driven updates to leadership.

Qualifications

• 5–10 years of experience managing software/AI delivery
• Experience with Agile methodologies (Scrum, Kanban, SAFe)
• Hands‑on backlog prioritization and release planning in fast‑moving environments
• Experience running retrospectives and driving measurable continuous improvement
• Strong planning, organization, and dependency management skills
• Solid documentation and process hygiene
• Strong analytical and problem‑solving abilities with delivery KPIs
• Excellent stakeholder communication across engineering, product, AI research, and leadership

Responsibilities

• AI Project Delivery: Drive delivery across ASR, TTS, speech intelligence, LLM apps, RAG pipelines, agentic workflows, conversational AI
• Agile Execution: Run Scrum/Kanban ceremonies including sprint planning, stand-ups, reviews, retrospectives, and backlog grooming
• Roadmap & Milestone Tracking: Maintain roadmaps, track milestones, and ensure visibility on timelines, risks, blockers, and dependencies
• Backlog Management: Prioritize backlog items based on customer impact, model performance gaps, dependencies, and business priorities
• Release Planning: Coordinate model, API, and product releases including readiness, QA status, evaluation results, and rollout plans
• Model Evaluation Coordination: Track evaluation activities (WER/CER, latency, MOS, accuracy, etc.) and real-world performance feedback
• Customer Feedback Loop: Build a structured feedback layer between users, customer-facing teams, product, and R&D for actionable tasks
• Cross-Team Collaboration: Connect Speech R&D, LLM, Platform Engineering, Product, QA, Data Engineering, MLOps, Delivery, Customer Success
• Risk & Dependency Management: Identify risks across data, model development, prompt engineering, deployment, and timelines; assign owners
• Documentation: Own project docs, meeting notes, decision logs, release notes, evaluation reports
• Metrics & Reporting: Track velocity, cycle time, release progress, model performance, customer issues, and KPI updates to leadership

Skills

Agile methodologies

Sprint planning

Backlog prioritization

Release planning

Roadmap tracking

Documentation

KPIs tracking

Stakeholder communication

Tools

Jira

Confluence

Linear

Azure DevOps

Job description

AI-Technical Project Manager (Speech& LLM team)

5 - 8 years experience

About the Role

research and Development knowledge and worked on Fast phase startup and knowledge on how Speech and LLM model works

Responsibilities

Project Manager – Speech AI & LLM Engineering

Speech AI Delivery | LLM Project Management | AI Engineering Execution | Cross-Functional Delivery

Location

Bangalore (Work from Office – 5 days)

Experience

5 to 8 years

Type

Full-Time

Reports To

VP of AI Engineering

About Gnani.ai

India's leading enterprise Voice AI company. 30M+ voice AI calls/day across 40+ languages. Deployed in BFSI, telecom, government, and enterprise. Backed by Samsung Ventures & Info Edge Ventures. Selected under the IndiaAI Mission to build foundational AI models for India.

The Role

We are hiring a Project Manager – Speech AI & LLM Engineering to drive planning, execution, and delivery across our Speech AI and LLM engineering workstreams.

This role is ideal for someone who can bring structure to fast-moving AI teams while understanding the basics of speech, language, and generative AI systems. You will work closely with Speech R&D, LLM teams, Engineering, Product, Delivery, QA, Data Engineering, MLOps, and Customer Success teams to ensure model development, product requirements, customer feedback, evaluation, and release timelines are aligned.

You will own sprint planning, backlog health, roadmap tracking, release coordination, dependency management, and cross-functional execution for ASR, TTS, speech intelligence, LLM applications, agentic workflows, and related AI capabilities.

What You Will Do

• AI Project Delivery: Drive delivery across ASR, TTS, speech intelligence, LLM applications, RAG pipelines, agentic workflows, conversational AI, and related AI capabilities.
• Agile Execution: Run Scrum/Kanban ceremonies including sprint planning, stand-ups, reviews, retrospectives, and backlog grooming across AI engineering squads.
• Roadmap & Milestone Tracking: Maintain the Speech AI and LLM roadmap, track milestones, and ensure clear visibility on timelines, risks, blockers, and dependencies.
• Backlog Management: Work with Speech R&D, LLM, Product, and Engineering leads to prioritize backlog items based on customer impact, model performance gaps, technical dependencies, and business priorities.
• Release Planning: Coordinate model, API, and product releases across teams, including release readiness, QA status, evaluation results, deployment dependencies, and customer rollout plans.
• Model Evaluation Coordination: Track evaluation activities for ASR, TTS, and LLM systems, including WER/CER, latency, MOS, accuracy, hallucination rate, response quality, task completion, safety, regression testing, and real-world performance feedback.
• Customer Feedback Loop: Build a structured feedback layer between model users, customer-facing teams, product teams, Speech R&D, and LLM teams so that production issues are converted into actionable engineering tasks.
• Cross-Team Collaboration: Act as the connective layer between Speech R&D, LLM teams, Platform Engineering, Product, QA, Data Engineering, MLOps, Delivery, and Customer Success teams.
• Risk & Dependency Management: Identify risks early across data, model development, prompt engineering, evaluation, infra, deployment, integration, and customer timelines; drive closure with clear owners and action items.
• Documentation: Own project documentation, meeting notes, decision logs, release notes, model improvement trackers, evaluation reports, and process artifacts.
• Metrics & Reporting: Track sprint velocity, cycle time, release progress, model performance metrics, customer issues, and delivery KPIs; provide data-driven updates to leadership.

Requirements

Must Have

• 5–10 years of experience managing software/AI engineering delivery, with strong exposure to Agile methodologies (Scrum, Kanban, SAFe)
• Proven track record of sprint planning, execution, and estimation across multiple engineering squads
• Hands‑on backlog prioritization and release planning in fast‑moving, cross‑functional environments
• Experience running retrospectives and driving measurable continuous improvement
• Strong planning & organization skills: prioritization, roadmap planning, milestone tracking, and dependency management
• Solid documentation, decision‑log, and process‑artifact hygiene
• Strong analytical, problem‑solving, and root‑cause thinking; comfort with delivery KPIs (velocity, cycle time, throughput)
• Excellent stakeholder communication across engineering, product, AI research, and leadership

Good to Have

• Certification in Scrum (CSM/PSM), SAFe (SA/SPC), or PMP/PMI-ACP
• Experience delivering ASR, TTS, LLM, RAG, or agentic/conversational AI products
• Familiarity with model evaluation metrics (WER/CER, MOS, latency, hallucination rate, task completion)
• Experience with tools like Jira, Confluence, Linear, or Azure DevOps
• Exposure to BFSI, telecom, healthcare, or enterprise product domains
• Familiarity with MLOps, data pipelines, APIs, cloud deployments, and CI/CD to converse fluently with AI and platform teams
• Experience setting up or scaling PMO practices in a startup environment

Why Join Gnani

You will bring order and momentum to teams building products used by millions — systems that process 30M+ real-time voice AI calls per day across BFSI, telecom, and government verticals. Your delivery discipline directly shapes how fast our Speech AI and LLM innovations reach production. You will work alongside engineering leaders, AI researchers, and product teams shaping proprietary multilingual speech and language technology.

The role has a clear growth path into Senior Project Manager, AI Delivery Lead, Engineering PMO Lead, or Director of Engineering Operations.

Skills Required

Primary Skills Lean Startup Thinking Research and development Agentic LLM Workflows People Management Speech & Generative AI