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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.
Work arrangement
No
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