Applied Scientist - Agentic AI
First seen by Alion on Sep 29, 2026.
About the Role:
Our client is an AI-first B2B2C platform transforming the Real Estate industry. We build intelligent, agentic, and automated solutions that improve productivity, accelerate sales velocity, and enable data-driven decision-making for developers, channel partners, and homebuyers.
Key Responsibilities:
- Build and ship chat, voice, and multimodal AI agents integrated into production products.
- Design agent workflows using LLMs, tools, memory, and state.
- Implement voice pipelines, including ASR, TTS, turn-taking, and interruptions.
- Work on Indian language voice agents, including latency and quality tuning.
- Develop workflow automation logic driven by agents.
- Build task execution systems where agents plan, act, and verify outcomes.
- Design and implement media and martech agents as part of product features.
- Build persona-based systems for content, campaigns, and engagement.
- Implement agent moderation and control mechanisms.
- Add observability, logging, and debugging for AI behavior.
- Reduce hallucinations and failure modes through system design.
- Collaborate closely with product, design, and engineering teams.
Qualifications and Skills:
- Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, Data Science.
- Hands-on experience building LLM-powered applications.
- Experience with chat agents or conversational systems.
- Understanding of tool calling, agent loops, memory, and state.
- Experience integrating AI, APIs and MCP's into backend or product workflows.
- Familiarity with voice AI systems or strong interest in building them.
- Ability to rapidly prototype and iterate on AI-driven features.
- Strong debugging mindset for real-world AI failures.
- Comfort working in fast-moving product environments.
Strong plus if you have experience with:
- Voice agents, speech-to-text, text-to-speech, telephony systems, Indian language NLP or speech systems.
- Workflow automation or agent orchestration frameworks.
- RAG systems, embeddings, and vector databases.
- Martech, CLM, campaign automation, or ad-tech workflows.
- Persona-based content or personalization systems.
- SaaS products with real users and scale constraints.
Skills
Machine Learning, Artificial Intelligence, Conversational AI, NLP, RAG, Agentic AI