AI Solutions Engineer

Position Overview:

We are seeking an AI Solutions Engineer to support the design, development, and deployment of enterprise AI solutions, with a strong emphasis on hands-on technical implementation.

This role focuses primarily on building, integrating, and optimizing AI systems such as Retrieval-Augmented Generation (RAG) pipelines, AI assistants, document intelligence solutions, while working under the guidance of senior solution architects.

This is an excellent opportunity for candidates looking to deepen practical experience in applied Generative AI within enterprise environments.

Responsibilities

AI Development & Implementation

• Build and maintain AI applications including:
  • RAG pipelines and knowledge assistants.
  • LLM integrations and prompt workflows.
  • Agentic AI bots
• Develop APIs, backend services, and integrations supporting AI solutions.
• Assist in optimizing model performance, inference latency, and system reliability.

Data & Knowledge Pipeline Engineering

• Prepare datasets for AI use cases including cleaning, structuring, and preprocessing.
• Manage vector databases, embeddings, and retrieval optimization.
• Support automation of data ingestion workflows.

Deployment & Operations Support

• Assist with deploying AI solutions across development, staging, and production environments.
• Monitor performance, troubleshoot issues, and optimize resource utilization.
• Support infrastructure setup (GPU inference environments, containers, cloud/on-prem deployments).

Internal Collaboration

• Work closely with solution architects and senior engineers.
• Support POC development, demos, and technical validation activities.
• Contribute to internal documentation and knowledge sharing.

Required Qualifications:

Technical Skills

• 5 - 10 years of relevant experience
• Practical experience with:
  • Python development (essential).
  • AI/ML frameworks or LLM integrations.
  • APIs, backend development, or automation scripting.
• Familiarity with:
  • Vector databases or semantic search concepts.
  • Data processing and document parsing workflows.
  • Containerization (Docker) or deployment environments.

Foundational Knowledge

• Understanding of Generative AI concepts (LLMs, embeddings, RAG basics).
• Basic database knowledge (SQL/NoSQL).
• Familiarity with Git-based development workflows.

Preferred Qualifications:

• Experience working on AI assistants, chatbots, or document AI projects.
• Exposure to GPU-based inference environments.
• Knowledge of cloud platforms or hybrid AI deployments.
• Experience with performance tuning or scaling AI systems.

Key Competencies:

• Strong technical curiosity and willingness to learn.
• Builder mindset and enjoys hands-on implementation.
• Detail-oriented and structured in approach.
• Ability to work independently with technical guidance.
• Practical problem-solving attitude.