Technical Delivery Manager

Oriserve; Dadri; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Oriserve is seeking a Forward Deployment Engineer who can own solution architecture, build full‑stack implementations, and configure AI systems in production.

You will lead Voice Bot and Chatbot delivery, coach pod leads to manage rather than do, and establish quality gates, while driving high ownership and accountability at scale.

This role requires urgency, clear communication, and the ability to empower teams to deliver reliable solutions for enterprise clients.

Qualifications

• Experience in enterprise integrations: REST APIs, webhooks, CRM connectivity.
• Produce and review architecture documents, sequence diagrams, and integration blueprints for complex client environments.
• Owned technical design decisions for client-facing deployments in Voice AI or conversational AI.
• Familiar with multi-system architectures: dialer integrations, IVR flows, real-time speech pipelines.

Responsibilities

• 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.
• Coach Voice Bot and Chatbot pod leads to shift from IC to manager — from doing to directing.
• 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.

Skills

Solution architecture

Team leadership

AI configuration

Full‑stack engineering

Python

MERN stack

Tools

REST APIs

Webhooks

CRM connectivity

Telephony platforms

SIP

WebRTC

Job description

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.

• 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.
• 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 escape 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.