Ignosis is a well-funded fintech infrastructure company building intelligent systems for the BFSI ecosystem. Backed by reputed investors, we focus on financial data intelligence, hyper-personalization, automation, and democratized credit access.

At Ignosis, we believe the next wave of fintech will be powered by AI systems that can think, speak, and act. We are building cutting-edge AI platforms that help financial institutions unlock deeper insights, automate complex workflows, and deliver smarter financial experiences.

Join us in building the future of AI-driven financial infrastructure.

Job Overview

We are building a production Voice AI Orchestrator a system where LLM agents listen, reason, and respond in real time across voice and messaging channels.

As an AI Engineer, you will design and build LLM-powered agent systems, orchestration frameworks, and real-time voice pipelines. This is not a wrapper role you will own the AI system architecture end-to-end, from agent design and evaluation to production reliability.

We are looking for engineers who have built and shipped AI systems in production, understand the challenges of non-deterministic LLM outputs, and enjoy solving complex real-world engineering problems.

Key Responsibilities

AI Agents & Orchestration

Design and build multi-agent systems using frameworks like LangGraph and LangChain.
Implement orchestration workflows with branching logic, retries, and parallel tool calls.
Build intelligent pipelines with custom tools, memory layers, and dynamic routing.

Voice AI Systems

Build real-time voice AI pipelines (STT ? LLM ? TTS) optimized for low latency.
Integrate telephony systems via Twilio, WebRTC, and SIP.
Engineer conversational voice experiences that perform reliably in production.

LLM Reliability & Evaluation

Design LLM evaluation pipelines including regression testing and adversarial evaluation.
Build guardrails, output validation, and fallback routing for reliable AI behavior.
Implement observability and monitoring for LLM systems.

Retrieval & Knowledge Systems

BuildRAG pipelinesfor intelligent knowledge retrieval
Implement hybrid search, re-ranking, and context compression strategies
Work with vector databases and embedding systems

Backend & System Integration

Integrate AI systems with Java / Spring Boot backend services
Implement WebSocket and asynchronous APIs for real-time agent communication.
Build scalable and reliable system architectures.

Experience

2+ years of software engineering experience
Experience building AI or LLM-based applications
Prior experience deploying LLM agents or AI pipelines into production environments

Agents Framework

Experience with one or more: LangChain/LangGraph/LlamaIndex/CrewAI/Haystack/Semantic Kernel

LLM Engineering

OpenAI APIs / GPT models
RAG (Retrieval-Augmented Generation)
Prompt engineering and context design
Function calling and structured outputs
LLM evaluation and reliability techniques

Voice AI

STT / TTS systems/Whisper/Deepgram/ Azure Speech/Google Speech/Real-time voice pipelines/Telephony integration (Twilio, WebRTC, SIP)

Backend

JavaSpring BootWebSocketsAsync / MultithreadingREST APIs

AI Infrastructure

Vector DatabasesEmbeddingsSemantic Search
PineconeQdrantWeaviateMilvusFAISS

Who We Are Looking For

Engineers who have shipped AI systems to production
Builders who think in systems latency, evaluation, reliability
People who understand that prompt engineering is engineering
Engineers comfortable working in fast-moving, ambiguous environments
Individuals who take full ownership from idea to production

Nice to Have

Experience with open-source LLMs (Llama, Mistral, Gemma)
Familiarity with LangSmith, Helicone, or LLM observability tools
Experience with real-time voice or telephony AI
Contributions to open-source AI tools

What's in it for you

Build cutting-edge AI systems combining LLMs, voice AI, and agent orchestration
Work on real-world fintech problems with top banks, NBFCs, and fintechs
Be part of a fast-moving startup building next-generation AI infrastructure
Competitive compensation and high ownership

To conclude, this role is ideal for engineers who want to build production-grade AI systems that think, speak, and act. At Ignosis, you will help shape the future of AI-powered fintech infrastructure.

To apply, send your resume to [HIDDEN TEXT]