AI Engineer - in Atlnata

Position: AI Engineer - Hybrid role in Atlnata
This job is with Finastra, an inclusive employer and a member of my Gwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

Who are we?
At Finastra, we are a dynamic global provider of open finance software solutions, dedicated to expanding access to financial services. Our innovative applications span Lending, Payments, Treasury and Capital Markets, and Universal Banking. Proudly serving over 8,000 customers, including 45 of the world's top 50 banks, we aim to boost financial inclusion for all. Join us and be part of a vibrant company that embraces diverse perspectives, and is committed to doing well by doing good.
We are seeking a motivated  AI Engineer  to design, implement, and deploy cutting-edge AI solutions powered by large language models (LLMs). This role focuses on building AI agents, RAG (Retrieval-Augmented Generation) systems, text-to-SQL applications, and other LLM-powered solutions.

You'll work with modern AI engineering tools and frameworks, collaborating with cross-functional teams to deliver innovative AI applications that drive real business value.
The ideal candidate is passionate about AI engineering, familiar with prompt engineering and RAG architectures, and eager to learn and grow in a fast-paced environment. You should have foundational experience with Python, LLM frameworks, and cloud platforms, and thrive in an Agile/Scrum development environment.

Key Responsibilities
AI Agent & LLM Application Development
Design and develop  AI agents  for task automation, decision-making, and workflow orchestration
Build  RAG (Retrieval-Augmented Generation)  systems using vector databases and semantic search
Implement  text-to-SQL  solutions to enable natural language database querying
Develop LLM-powered applications for summarization, content generation, data extraction, and conversational AI
Apply  prompt engineering  and  context engineering  techniques to optimize LLM performance
Implement  function calling  and  tool use  patterns for agentic workflows
AI Pipelines & Deployment
Build and maintain AI workflows and pipelines using  Lang Chain ,  Lang Graph , or  CrewAI
Deploy and manage LLM solutions on  Azure OpenAI ,  AWS Bedrock , or similar cloud platforms
Implement  observability  and monitoring for AI systems to track performance, costs, and reliability
Automate model deployment and orchestration using CI/CD pipelines
Collaboration & Best Practices
Participate in daily stand-ups, sprint planning, and retrospectives in an  Agile/Scrum  environment
Use  Git Hub  for version control and collaborate through pull requests and code reviews
Build and maintain  Git Hub Actions  workflows for automated testing and deployment
Work closely with stakeholders to translate business requirements into AI solutions
Document AI architectures, prompt strategies, and system designs for team knowledge sharing

Required Qualifications
Programming:  Strong proficiency in  Python  for AI/ML development
LLM Fundamentals:  Understanding of large language models, their capabilities, and limitations
AI Engineering Techniques:  Knowledge of prompt engineering, context engineering, RAG patterns, and LLM observability
AI Frameworks:  Hands-on experience with at least one framework:  Lang Chain ,  Lang Graph ,  CrewAI , or similar
Vector Databases:  Familiarity with vector stores (Pinecone, Weaviate, Chroma

DB, FAISS, etc.) for embeddings and retrieval
Software Development:  Understanding of Git workflows, version control with  Git Hub , and software development best practices

Collaboration:

Experience working in  Agile/Scrum  teams with sprint-based development
Strong problem-solving skills and ability to learn new technologies quickly

Preferred Qualifications

Experience with  C#  for application integration
Hands-on experience with  Azure OpenAI Service ,  Azure AI Search , or other Azure AI services
Experience leveraging Databricks' data and AI platform
Familiarity with  AWS Bedrock  and other cloud AI platforms
Knowledge of  CI/CD pipelines  and  Git Hub Actions  for automation

Experience with  LLM evaluation frameworks  and performance testing
Understanding of  semantic…