AI Engineer-Voice AI, LLM Agents & Orchestration

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 environmentsAgents 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 Java · Spring Boot · WebSockets · Async / Multithreading · REST APIs AI Infrastructure Vector Databases · Embeddings · Semantic Search Pinecone · Qdrant · Weaviate · Milvus · FAISSWho 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 productionNice 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 toolsWhat’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 ownershipTo 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

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