Forward-Deployed AI Engineer

We are looking for a highly skilled Generative AI / AI Agent Engineer/ Forward Engineer to design, develop, deploy, and maintain AI-powered applications and intelligent agent-based solutions.
The ideal candidate will have strong experience with Python, Generative AI, LLMs, AI Agents/Agentic AI, RAG, Vector Databases, APIs, and cloud-based AI/ML deployment. You will work closely with product, engineering, and business teams to transform AI concepts and POCs into scalable, reliable, production-ready solutions.
Key Responsibilities
Design and develop Generative AI and LLM-powered applications using Python.
Build intelligent AI Agents / Agentic AI workflows capable of reasoning, tool usage, task execution, and automation.
Develop and optimize Retrieval-Augmented Generation (RAG) solutions using vector databases.
Integrate LLMs with enterprise applications, databases, APIs, and external services.
Design and develop AI applications and automation workflows for business use cases.
Develop REST APIs and system integrations to connect AI solutions with existing platforms.
Work with different LLM models, prompting techniques, embeddings, context management, and evaluation approaches.
Implement scalable AI/ML solutions using Docker and cloud platforms.
Deploy, monitor, troubleshoot, and maintain AI/ML applications in production environments.
Optimize AI applications for performance, reliability, scalability, and cost.
Collaborate with engineering and product teams to understand requirements and translate them into technical AI solutions.
Troubleshoot application, integration, infrastructure, and AI/ML-related issues.
Establish appropriate logging, monitoring, testing, and error-handling mechanisms for production AI applications.
Take AI solutions from Proof of Concept (POC) through production deployment.
Stay current with emerging technologies in Generative AI, LLMs, Agentic AI, RAG, and AI application development.
Required Skills
Programming
Strong proficiency in Python.
Experience developing production-grade applications and services.
Strong understanding of APIs, JSON, REST, and system integrations.
Generative AI / LLM
Hands-on experience with Generative AI and Large Language Models (LLMs).
Experience with LLM application development, prompt engineering, embeddings, and context management.
Familiarity with commercial and/or open-source LLM platforms and models.
AI Agents / Agentic AI
Experience building AI Agents / Agentic AI systems.
Understanding of agent workflows, tool/function calling, multi-step reasoning, orchestration, and autonomous task execution.
Experience integrating AI agents with APIs, databases, enterprise systems, or external tools.
RAG & Vector Databases
Hands-on experience implementing RAG architectures.
Experience with embeddings, document processing, chunking, retrieval, reranking, and context optimization.
Experience working with Vector Databases such as Pinecone, Weaviate, Milvus, Qdrant, Chroma, FAISS, or equivalent.
APIs & System Integration
Strong experience developing and consuming REST APIs.
Experience integrating AI solutions with enterprise applications, databases, SaaS platforms, and third-party services.
Understanding of authentication, authorization, API security, and data exchange.
Cloud & Deployment
Experience with Docker and containerized application deployment.
Experience with one or more cloud platforms such as AWS, Azure, or GCP.
Understanding of AI/ML deployment, cloud infrastructure, and production environments.
Experience with CI/CD and deployment automation is a plus.
Preferred Qualifications
Experience taking AI solutions from POC to production.
Experience with AI Agent frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Semantic Kernel, or similar.
Experience with ML/AI frameworks such as PyTorch, TensorFlow, or Hugging Face.
Experience with Kubernetes is a plus.
Experience with MLOps/LLMOps practices is a plus.
Experience with AI evaluation, observability, monitoring, and guardrails.
Experience working with enterprise data and security requirements.
Education
Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, Engineering, or a related field.
Key Competencies
Strong problem-solving and analytical skills.
Ability to convert business requirements into practical AI solutions.
Strong communication and collaboration skills.
Ability to work independently in a fast-paced environment.
Strong focus on automation, reliability, scalability, and production quality.
Passion for emerging Generative AI and Agentic AI technologies.

Work arrangement
Yes