About the role

Company Description

We are an AI-native company that partners with enterprises and growth-stage organizations to help them become AI-driven across products and operations. Our team focuses on accelerating AI adoption by identifying high-impact use cases and implementing solutions that improve internal efficiency and user experience. We design and build AI systems that enhance end-user and customer journeys, ensuring measurable business outcomes. We combine deep technical expertise with a consultative approach, working closely with clients to modernize their technology stack and leverage AI at scale.

Role Description

We are looking for a highly motivated Full Stack AI Engineer (Forward Deployed Engineer) to work closely with customers, product teams, and engineers to build and deploy AI-powered solutions that solve real-world business problems.

As a Full Stack AI Engineer, you will combine software engineering, customer-facing problem solving, and AI implementation skills. You will work directly with clients to understand requirements, develop custom workflows, integrate AI solutions, and rapidly deliver production ready applications.

The ideal candidate has hands-on experience with Python, React, APIs, and AI/LLM technologies, along with strong communication and stakeholder management skills.

Key Responsibilities

Work directly with customers to understand business processes, pain points, and technical requirements.
Design and develop custom AI-powered applications and workflows.
Build scalable backend services using Python.
Develop modern front-end interfaces using React.js.
Integrate third-party APIs, enterprise systems, and data sources.
Deploy and customize AI solutions based on Large Language Models (LLMs).
Create, evaluate, and optimize prompts for business use cases.
Build conversational AI systems, copilots, knowledge assistants, and intelligent automation workflows.
Collaborate with Product, Engineering, and Customer Success teams to deliver solutions quickly.
Troubleshoot customer issues and provide technical guidance during implementations.
Participate in client meetings, solution workshops, and technical discussions.
Document solutions, integrations, and implementation approaches.

Required Skills

Software Engineering

Strong proficiency in Python.
Experience with FastAPI, Flask, or Django.
Experience building and consuming REST APIs.
Good understanding of software architecture and design principles.
Knowledge of SQL and database design.

Frontend Development

Hands-on experience with React.js.
Strong knowledge of JavaScript, HTML, and CSS.
Experience integrating frontend applications with backend services.

AI & LLM Technologies

Experience working on AI, Generative AI, or LLM-based projects.
Understanding of Prompt Engineering techniques.
Experience with OpenAI, Gemini, Claude, Llama, or similar models.
Familiarity with LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or equivalent frameworks.
Understanding of Retrieval-Augmented Generation (RAG).
Experience building AI assistants, chatbots, or workflow automation systems.

Customer-Facing Skills

Strong communication and presentation skills.
Ability to gather requirements and translate business needs into technical solutions.
Experience working directly with stakeholders and customers.
Strong problem-solving and analytical thinking abilities.

Preferred Qualifications

Bachelor's degree in Computer Science, Engineering, Information Technology, or related field.
2 - 5 years of software development experience.
Experience in customer-facing engineering, solutions engineering, implementation consulting, or technical consulting roles.
Exposure to enterprise software integrations.

Nice to Have

Experience with Docker and containerization.
Familiarity with AWS, Azure, or GCP.
Knowledge of CI/CD pipelines.
Experience with vector databases such as Pinecone, FAISS, Weaviate, or ChromaDB.
Understanding of AI Agents and multi-agent architectures.
Exposure to data pipelines and workflow orchestration tools.

What Success Looks Like

Ability to understand customer challenges quickly.
Deliver AI-powered solutions with minimal supervision.
Build reliable, scalable applications that create measurable business impact.
Act as the bridge between customers, product teams, and engineering teams.
Drive successful deployment and adoption of AI solutions.