Technical Delivery Manager
Enterprise Voice AI & Chatbot Delivery · Noida (In-Office)
Function - Delivery — reports to Head of Delivery
Location - Noida (In-Office)
Seniority - Senior People Manager (8–14 years)
Teams Governed - Voice Bot Delivery Pods · Chatbot Delivery Pods
Core Stack - Python · MERN Stack · Voice AI (STT / TTS / LLM / Speech-to-Speech) · Telephony · LLMs · SLMs · RAG
Sectors - BFSI · Telecom · Auto · Enterprise — India, Middle East & Europe
WHY THIS ROLE EXISTS
We have strong technical delivery pods with real AI and engineering talent. What we need now is a leader who sets the quality bar across both Voice Bot and Chatbot delivery — and holds the teams to it.
Our delivery teams need to operate as Forward Deployment Engineers: part Solution Architect, part Full-Stack Engineer, part Applied AI practitioner. This person builds that culture and enforces that standard.
The problems this role solves:
- Technical quality is inconsistent — deployments require more rigorous review before reaching production.
- Work distribution across pods needs active management — capacity, utilisation, and challenge levels are uneven.
- Pod leads have strong individual contributor instincts and need coaching toward true team management.
- No succession pipeline exists — the next generation of technical leaders is not yet being built.
- Delivery timelines directly impact client revenue outcomes — a high-agency, high-accountability operating culture is non-negotiable at this scale.
THE MANDATE
You own two things: technical quality across all delivery, and the development of the people doing it. These are inseparable.
1. Technical Quality Enforcement
- Own the technical bar for every voice bot and chatbot deployment — from solution design through go-live to steady-state operations.
- Review integrations, conversation flow designs, AI model configurations, API contracts, and telephony setups before they reach production.
- Act as solution architect on complex client integrations — coach the team on how to design and deliver correctly, not do it for them.
- Call out what is wrong, clearly and early. Not after the client notices.
- Own the deployment checklist, the quality gate, and the go-live sign-off process.
2. Team Development & Succession
- Coach Voice Bot and Chatbot pod leads to shift their operating mode from individual contributor to manager — from doing to directing.
- Identify 2–3 high-potential team members across pods and actively develop them toward next-level roles.
- Distribute work with intent: right people on right projects, capacity balanced, everyone operating at full potential.
- Build a Forward Deployment Engineer culture — every delivery team member should be capable of owning solution design, full-stack implementation, and AI configuration end-to-end on their accounts.
- Set clear expectations on quality, accountability, and escalation. No zombie projects. No polite silence about problems.
3. High-Agency Operational Rhythm
Delivery at this scale requires a team that moves with urgency and ownership, not one that waits for direction. Your job is to build that.
- Establish and own the weekly technical delivery review across Voice Bot and Chatbot functions.
- Maintain full visibility into all active deployments — health, blockers, and risk to go-live or production stability.
- Instil a direct link between delivery speed and client revenue outcomes. Every slip is a client revenue impact — the team must internalise this.
- Flag RED projects within 48 hours of trigger. Escalate to Head of Delivery with a clear recommendation, not just a problem statement.
- Drive a zero-zombie-project culture — every project has an active committed date or a kill decision, no exceptions.
- Coordinate with product and engineering when platform or AI issues affect delivery — be the technical interface between the delivery team and product/tech.
WHAT WE'RE LOOKING FOR
The profile we're building toward across the delivery team is the Forward Deployment Engineer: someone who can own solution architecture, build or deeply understand full-stack implementation, and configure and evaluate AI systems in production. This role sets that standard and builds it into the culture.
Solution Architecture — You can design, not just describe
- Experienced in designing enterprise integrations: REST APIs, webhooks, CRM connectivity, telephony platforms, event-driven systems.
- Can produce and review solution architecture documents, sequence diagrams, and integration blueprints for complex client environments.
- Has owned technical design decisions for client-facing deployments in Voice AI or conversational AI — not just reviewed them.
- Comfortable with multi-system architectures: dialler integrations, IVR flows, real-time speech pipelines, callback and retry logic.
Applied AI Depth — You understand AI delivery, not just AI theory
- Familiar with LLM-based conversational AI: prompt structure, model behaviour, hallucination patterns, latency trade-offs, and retrieval-augmented generation (RAG).
- Understands voice bot architecture: the STT → LLM → TTS pipeline (including Speech-to-Speech), turn-taking, interruption handling, and conversation flow logic.
- Can evaluate whether a deployed voice bot or chatbot is configured correctly at the production delivery level — not at the research level.
- Familiar with LLMs, SLMs, and when to use each. Experience with AI evaluation, quality scoring, and production monitoring is a strong plus.
Full-Stack Engineering Grounding — You've built, not just managed builds
- Strong engineering foundation across Python and MERN stack — sufficient to read code, review architectures, and challenge technical decisions with specificity.
- Comfortable with cloud environments, deployment pipelines, and production observability.
- Not expected to write production code in this role — but must be credible and precise when reviewing it.
- Has worked with telephony infrastructure (SIP, WebRTC, or similar) and understands real-time system constraints.
People Leadership — This is your primary job
- Has managed technical delivery teams before. Can show specifically how someone's output improved because of how you managed and developed them.
- Has coached individual contributors toward management — the shift from doing to directing.
- Has built team structures: defined roles, distributed work with intent, created accountability without micromanaging.
- Operates with high agency — does not wait to be told what to fix. Identifies problems, proposes solutions, and acts.
- Does not default to solving technical problems themselves when the team is stuck. Coaches first. Steps in only when truly needed.
Character Filters — Non-negotiable
- High ownership: you treat delivery outcomes as your own, not the team's problem to manage.
- Bias for directness: you say what is wrong, to the right person, at the right time. No soft-pedalling quality issues.
- Comfortable with ambiguity: Oriserve is scaling fast — processes are being built, not inherited.
- Enterprise sensibility: understands what BFSI, Telecom, and Auto clients expect at scale, and why cutting corners is not a trade-off.
- Urgency without chaos: knows how to move fast, make decisions under pressure, and keep the team steady.
WHAT SUCCESS LOOKS LIKE
First 30 Days
- Deep familiarity with every active client deployment across Voice Bot and Chatbot — what's live, what's in progress, what's at risk.
- First technical review conducted with each pod. Initial quality gaps and work distribution issues documented.
- Clear picture of team capacity: who is overloaded, who is underutilised, where the skills gaps are.
60–90 Days
- Technical quality review cadence established and running. Every deployment has a review owner and a sign-off checkpoint.
- Pod leads operating with clearer delegation — less doing, more directing.
- First succession plan drafted: 2–3 names identified with a development path outlined.
- Zero production incidents attributable to inadequate pre-deployment review.
6 Months
- Pods are self-correcting — team members flag quality issues before they escalate to you.
- Go-live velocity improves: fewer slips, faster recovery when slips happen.
- Pod leads are managing, not executing. You're developing them, not replacing them.
- At least one team member is visibly ready for a step-up in responsibility.
- The Forward Deployment Engineer standard is visible in how the team approaches new client onboardings.
WHAT THIS ROLE IS NOT
If your instinct when a delivery is struggling is to jump in and fix it yourself — this is not the right role. The job is to build people who fix it, and systems that prevent it from breaking in the first place.
- Not a project manager. The Head of Delivery owns client program management and timelines. You own technical quality and team development.
- Not a senior IC. You will not be the person designing prompts, building integrations, or configuring bots for clients on an ongoing basis.
- Not a co-delivery resource. You own a quality and coaching function — not a headcount buffer for busy delivery periods.
WHY JOIN ORISERVE
- You will be one of the most technically senior people in the delivery organisation — with real authority to set the quality bar and enforce it.
- Oriserve operates at genuine enterprise scale: 30 Mn+ AI voice interactions and 10 Mn+ chats every month across marquee BFSI, Telecom, and Auto clients in India and internationally.
- You will build the technical delivery function from the ground up — the team structure, quality processes, and succession pipeline. This is a builder role, not a maintenance role.
- Direct visibility to the founding team. Your mandate is clear and your impact is measurable quarter-on-quarter.
- Competitive compensation + ESOP in a company at pre-Series A inflection with strong fundamentals.
To explore this opportunity, reach out at [Confidential Information] ·
Subject: Technical Delivery Manager
