What are the responsibilities and job description for the Generative AI Engineer position at Baanyan Software Services, Inc.?
You are a builder at heart with a "hacker" mindset and a passion for revenue operations. You are eager to bridge the gap between raw model capabilities and polished tools that actually help sales teams win. You are proactive, iterate quickly, and enjoy the challenge of "taming" non-deterministic AI outputs in high-stakes, real-time environments.
You will be working to design, deploy, and optimize Generative AI solutions that eliminate friction in our Go-To-Market (GTM) engine. You will move beyond traditional data analytics and modeling to build agentic workflows and RAG (Retrieval-Augmented Generation) systems, applying the latest advancements in Foundation Models to create intuitive, AI-native tools that supercharge our sales and marketing teams.
- Master’s degree or equivalent experience in Computer Science, Engineering, or a related technical field.
- Strong proficiency in Python/TypeScript and experience building web services or integrating complex APIs (especially CRM, VoIP, or sales engagement platforms).
- Solid understanding of the LLM stack, including experience with orchestration frameworks (e.g., LangChain/LangGraph, Strands Agents, CrewAI).
- Knowledge of modern AI concepts: Prompt Engineering, few-shot learning, and the difference between fine-tuning and RAG.
- Experience with standard software development tools (Git, Docker) and CI/CD processes.
- A product-oriented and revenue-focused mindset: the ability to deeply empathize with a BDR's workflow and design AI outputs that are instantly actionable during a live call.
- Evangelist Energy: You are genuinely excited about AI. You follow the latest releases, read the relevant papers, and can explain why "reasoning models" matter to a non-technical sales stakeholder.
- Fearless "Hacker" Mindset: You aren't afraid of code you didn't write. You are comfortable generating 80% of your code with AI and crafting the remaining 20% with high precision.
- Even better if you have one or more of the following:
- Domain expertise in Go-To-Market, RevOps, or Sales tech stacks (Salesforce, Hubspot, Gong, Apollo, Clearbit).
- Experience building real-time audio/speech-to-text processing pipelines (e.g., WebRTC, Deepgram, Whisper) for live transcription and analysis.
- Contributions to open-source AI projects or a portfolio of "weekend" prototypes built with an AI-native toolchain.
- Exposure to cloud-based AI services (e.g., AWS Bedrock, Azure AI Studio, or GCP Vertex AI).
- Experience with Vector Databases and semantic search concepts.
- Experience with AI evaluation and observability tools.
- Knowledge of "agentic" design patterns.