Technical Project Manager

Bigship; Dehradun; On-site; INR 1,800,000 - 3,000,000; Full time

Benefits offered by this job

GPU compute resources

AI research budget

Flexible working arrangements

Job summary

Bigship in India is seeking an experienced engineer to lead Voice AI development and infrastructure. The role covers building real-time voice agents, end-to-end ASR/TTS/NLU pipelines, and low-latency production-grade systems.

You will design scalable in-house tooling, collaborate across teams, and mentor engineers while delivering robust voice-enabled features.

Qualifications

• 5 years of total software development experience.
• Minimum 1 year of hands-on experience building and deploying AI agents in production.
• Proven track record of in-house AI/ML solutions with limited external SaaS dependencies.

Responsibilities

• Design and build real-time voice-based AI agents capable of natural, low-latency conversations.
• Develop and integrate ASR, TTS, and NLU pipelines in-house.
• Implement wake-word detection, speaker diarization, noise cancellation, and VAD modules.
• Build dialogue management with context tracking and multi-turn flows.
• Optimize ASR/TTS models for accuracy and latency.

Tools

Python

PHP-Laravel

Docker

Kubernetes

AWS

GCP

Azure

ONNX

TensorRT

Triton Inference Server

Kafka

RabbitMQ

Redis Streams

PostgreSQL

Redis

Pinecone

Weaviate

Qdrant

WebSockets

WebRTC

Job description

Role & responsibilities

Voice AI Development

• Design and build real-time voice-based AI agents capable of natural, low-latency conversations.
• Develop and integrate Automatic Speech Recognition (ASR), Text-to-Speech (TTS), and Natural Language Understanding (NLU) pipelines entirely or predominantly in-house.
• Implement wake-word detection, speaker diarization, noise cancellation, and voice activity detection (VAD) modules.
• Build dialogue management systems with context tracking, intent handling, and multi-turn conversation flows.
• Optimize ASR/TTS models for accuracy, latency, and domain-specific vocabulary.

Infrastructure & Platform Engineering

• Design and manage the cloud or on-premise infrastructure required to deploy, scale, and monitor voice AI workloads.
• Set up CI/CD pipelines, containerization (Docker/Kubernetes), and model serving infrastructure (e.g., Triton, TorchServe, custom gRPC services).
• Ensure high availability, fault tolerance, and low-latency performance of real-time voice systems.
• Implement logging, monitoring, and alerting for production AI systems.
• Reduce dependency on external vendors by building reusable, internal libraries and services.

In-House Solution Design

• Evaluate open-source ASR (e.g., Whisper, Wav2Vec2, Kaldi), TTS (e.g., Coqui, VITS, FastSpeech2), and LLM frameworks and adapt them for production use.
• Build custom model training and fine-tuning pipelines for domain-specific voice applications.
• Contribute to internal tooling, SDKs, and APIs that allow other teams to build voice-powered features.

Collaboration & Leadership

• Collaborate with product, design, and data teams to translate business requirements into technical solutions.
• Conduct code reviews, mentor junior engineers, and enforce engineering best practices.
• Document architecture decisions, APIs, and operational runbooks.

Required Qualifications

Experience

• 5 years of total software development experience.
• Minimum 1 year of hands-on experience building and deploying AI agents in a production environment.
• Proven track record of building in-house AI / ML solutions with limited dependency on external SaaS platforms.

Technical Skills Voice AI

• Strong experience with ASR systems: Whisper, Wav2Vec2, DeepSpeech, Kaldi, or equivalent.
• Experience with TTS engines: Coqui TTS, VITS, FastSpeech2, Mozilla TTS, or equivalent.
• Hands-on experience with NLU/dialogue frameworks: Rasa, custom transformer-based models, or similar.
• Familiarity with audio processing libraries: librosa, PyDub, SpeechBrain, WebRTC VAD.
• Understanding of real-time audio streaming protocols (WebSockets, WebRTC, SIP/VoIP).

Technical Skills – Infrastructure

• Proficiency with Python and worked around 1 year in PHP-Larvel.
• Experience with Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure).
• Familiarity with ML model serving and optimization (ONNX, TensorRT, Triton Inference Server).
• Experience with message brokers and streaming platforms (Kafka, RabbitMQ, or Redis Streams).
• Working knowledge of databases: PostgreSQL, Redis, and vector databases (Pinecone, Weaviate, or Qdrant).

Good to Have

• Experience with on-device / edge AI for voice (TFLite, CoreML, ONNX Runtime).
• Familiarity with telephony stacks and VoIP platforms (Asterisk, FreeSWITCH, Twilio Programmable Voice).
• Experience fine-tuning LLMs (LLaMA, Mistral, Falcon) for conversational use cases.
• Contributions to open-source voice AI or ML projects.

What We Offer

• Opportunity to build a cutting-edge voice AI platform from the ground up.
• High ownership, low bureaucracy your decisions directly shape the product.
• Competitive compensation and performance-linked incentives.
• Flexible working arrangements.
• Access to GPU compute resources and a dedicated AI research budget.