AI Analytics Engineer

Solve IT Consultant is seeking an AI Analytics Engineer to build and deploy AI/LLM solutions, including RAG systems and autonomous workflows. The role focuses on automating financial and data processes, integrating AI with enterprise platforms, and ensuring deployed systems are reliable, scalable, and secure.

Responsibilities:

• Architect and develop end-to-end AI/LLM solutions using LangChain and modern frameworks
• Design and implement RAG-based systems for financial data processing and insight generation
• Build and orchestrate multi-step AI workflows and autonomous agents using LangGraph or similar tools
• Develop AI-driven automation pipelines to replace manual financial and data processes
• Write efficient, scalable Python code for AI workflows, data processing, and integrations
• Design and optimize complex SQL queries for large-scale data extraction, validation, and transformation
• Integrate AI systems with enterprise platforms, APIs, and data warehouses
• Develop evaluation frameworks for model accuracy, performance, and compliance
• Implement hallucination detection, monitoring, and output validation strategies
• Collaborate with business and technical stakeholders to identify AI-driven transformation opportunities
• Ensure scalability, security, and performance of deployed AI systems

Requirements:

• Local preferred
• Strong hands-on experience with LangChain and LLM ecosystems
• Build complete LLM pipelines (ingestion → processing → output)
• Manage chains, agents, tools, and memory
• Deliver production-grade AI applications
• Strong proficiency in Python programming
• Building AI/ML pipelines and backend services
• Data processing using libraries (Pandas, NumPy, etc.)
• API development (FastAPI/Flask)
• Writing clean, scalable, and production-ready code
• Proven experience building RAG-based AI systems
• Strong understanding of: Data ingestion and chunking strategies
• Embeddings and vector databases
• Context orchestration (retrieve → reason → respond)
• Strong expertise in SQL (mandatory)
• Write complex queries (joins, window functions, aggregations)
• Perform data validation and reconciliation
• Work with large-scale financial datasets
• Data pipelines and ETL/ELT processes
• Data modeling and schema design
• Experience with LangGraph or similar frameworks
• Design multi-step reasoning workflows
• Orchestrate LLMs, APIs, and tools in decision pipelines
• Ability to transform financial workflows using AI-driven automation
• Source-to-target data mapping automation
• Metadata extraction (e.g., information schema)
• Semantic matching and fuzzy logic
• Leveraging logs and historical data for intelligent outputs
• AI evaluation frameworks
• Output validation and monitoring systems
• Hallucination detection and mitigation strategies
• Strong experience with: REST APIs and third-party integrations
• Data services and microservices architecture
• Integrate AI solutions with enterprise systems
• Process structured and unstructured data
• Model Context Protocol (MCP) or similar frameworks
• Deployment environments and server configurations
• Experience deploying AI solutions beyond notebooks into production environments
• Strong ownership and ability to work independently
• Proven track record of solving complex, ambiguous problems
• Experience delivering end-to-end AI systems with minimal supervision