Build and ship AI-powered product features using LLMs, NLP, and agent-based workflows Develop backend services and APIs that support model inference, orchestration, and tool execution Implement LLM workflows, including pipelines, retrieval (RAG) systems, and goal-oriented agent behaviors Work closely with Product Managers and Designers to turn AI-driven ideas into working features Collaborate with ML engineers to integrate, evaluate, and productionize models Write clean, maintainable, and well-tested code Participate in code reviews and contribute to technical discussion Help improve system performance, reliability, and scalability 1-2 years of professional software engineering experience Strong experience building backend or full-stack applications Proficiency in Python and at least one other language (Java, Go, or TypeScript) Hands-on experience integrating LLMs, NLP, or ML-powered features Familiarity with APIs, distributed systems, and backend services Understanding of prompting, embeddings, and model inference Solid software engineering fundamentals (testing, debugging, system design) Product mindset with a focus on real-world impact and usability Experience with agentic systems, workflows, or orchestration frameworks Exposure to RAG Architecture Design & Evaluation Experience working in AI-first or fast-moving product teams Experience our comprehensive benefits with family medical, vision and dental coverage, a competitive base salary, and eligibility for equity awards and discretionary bonuses or commissions.

Lead the team in: research, design, development, and deployment of advanced AI agents and agentic systems. Architect and implement complex multi-agent systems, including planning, decision-making, and execution capabilities. Develop and integrate large language models (LLMs) and other state-of-the-art AI techniques to enhance agent autonomy and intelligence. Build robust, scalable, and reliable infrastructure to support the deployment and operation of AI agents at scale. Diagnose and troubleshoot issues in complex distributed environments and optimize system performance. Contribute to the team's technical growth and knowledge sharing. Stay up-to-date with the latest advancements in AI research and agentic AI and apply them to our products. Leverage enterprise data, market data, and user interactions to build intelligent and personalized agent experiences. Knowledge and passion in machine learning algorithms, Gen AI, LLMs, and natural language processing (NLP). Understanding of agent-based modeling, reinforcement learning, and autonomous systems. Ability to innovate, as proven by a track record of software artifacts or academic publications in applied machine learning. Experience with large language models (LLMs) and their applications in Agentic AI. Proficiency in programming languages such as Python, and experience with machine learning frameworks like TensorFlow or PyTorch. Experience with cloud platforms (AWS) and containerization technologies (Docker, Kubernetes). Understanding of distributed system design patterns and microservices architecture. Excellent problem-solving and data analysis skills. Strong communication and collaboration skills. Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related field, or equivalent years of experience. Min 5-7+ years of relevant work experience in AI, Machine Learning, and applying data science to real-world use cases. OR Strong track record of taking systems from prototype to production with a focus on scalability and reliability. Knowledge of fine-tuning strategies (QLORA, DPO) and inference optimization (vLLM, TensorRT-LLM). Research experience in agentic AI or related fields. Experience building and deploying AI agents in real-world applications. Experience our comprehensive benefits with family medical, vision and dental coverage, a competitive base salary, and eligibility for equity awards and discretionary bonuses or commissions.