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Mission
seeking an experienced AI Engineer to join our fast-growing team. In this role, you will design, train, and deploy AI models to solve real-world problems. You will work closely with cross-functional teams, including software engineers, DevOps engineers, and product managers, to integrate intelligent features into our platform and services.
Responsibilities
LangChain/LangGraph Development: Build and maintain modular, scalable LLM-powered agents and tools using LangChain and/or LangGraph.
Retrieval-Augmented Generation (RAG): Implement RAG-based solutions to improve AI responses using external knowledge bases.
API & Backend Integration: Work with software engineers to integrate AI systems into backend infrastructure and expose them via APIs.
AI Agent Development: Design, build, and deploy autonomous AI agents that can reason and execute multi-step tasks using LLMs, tools, memory, and APIs.
Experimentation & Evaluation: Continuously refine models using A/B testing, human feedback loops, and AI evaluation metrics.
Stay Updated: Keep up with the latest LLM advancements and best practices in the AI industry.
Product applications: Apply LLMs and agents to real-world scenarios that solve meaningful user problems.
Product implementation: Work closely with the product team to ensure that delivery is aligned with expected product requirements
Response validation: Implement a process to ensure accurate KPI measurement and consistent, expected outcomes.
Typescript Integration: (Preferred) Help implement and maintain AI modules and integrations using Typescript-based stacks.
2+ years of experience as an AI engineer or applied ML engineer working with LLMs (e.g. OpenAI, Claude, Mistral, etc.).
Proven experience with LangChain and/or LangGraph to build real-world AI agents or workflows.
Proficiency in Python/Type script, with hands-on experience in LLM frameworks and orchestration tools.
Experience designing and deploying autonomous agents, memory modules, and tool-using systems.
Familiarity with vector databases (FAISS, Pinecone, Weaviate, etc.) and knowledge retrieval systems.
Solid understanding of NLP workflows, prompt engineering, and tokenization strategies.
Experience with RESTful APIs and backend data integration.
Strong debugging, problem-solving, and architectural design skills.
Experience with Typescript, especially in AI agent or tool integration.
Prior experience deploying AI in production systems.
Familiarity with MLOps and CI/CD pipelines for AI-based applications.
Experience working with cloud platforms (AWS / GCP, or Azure).
MSc in Machine Learning, Computer Science, or a related technical field.
