AI Engineer- remote

Mission

Design build and deploy enterprise-grade AI solutions autonomous AI agents and multi-agent orchestration frameworks that support digital transformation initiatives with a focus on financial services anti-financial crime processes and scalable AI platforms. Contribute to the development of secure reliable and production-ready AI capabilities that enable organizations to leverage Generative AI and LLM technologies at scale.

Responsibilities:

• Architect and develop production-grade autonomous agents and multi-agent orchestration frameworks (e.g. LangChain AutoGen CrewAI).
• Design build and deploy AI solutions based on Large Language Models (LLMs) and agentic architectures.
• Guide technical implementations across multiple parallel squads ensuring consistent and reusable architectural standards.
• Integrate LLMs with external APIs proprietary tools databases and enterprise systems to enable advanced tool-calling capabilities.
• Optimize prompt engineering approaches context management state management and long-running agent workflows.
• Implement monitoring logging evaluation and observability frameworks for AI applications and autonomous agents.
• Apply MLOps/AIOps practices including model versioning testing performance evaluation and monitoring.
• Design and deploy AI solutions on cloud platforms primarily AWS while collaborating on Azure and Databricks environments where applicable.
• Collaborate with business data science engineering and cloud teams to deliver AI-powered solutions in regulated environments.

Qualifications :

Professional Experience

• 5-10 years of professional experience in AI Engineering Software Engineering Machine Learning or related fields.
• Experience designing and implementing enterprise AI solutions.
• Experience building and deploying autonomous AI agents and multi-agent systems.
• Experience integrating Generative AI and LLM technologies into enterprise applications.

Technical Skills

• Strong Python development skills.
• Hands-on experience with AWS including AWS Bedrock and AgentCore.
• Experience with AI/LLM integration patterns such as:
  • MCP (Model Context Protocol)
  • A2A (Agent-to-Agent communication)
  • Structured Outputs
  • Skills-based architectures
• Knowledge of agent orchestration frameworks such as LangChain AutoGen CrewAI or similar.
• Experience with MLOps/AIOps practices:
  • Versioning
  • Testing
  • Monitoring
  • Evaluation frameworks
• Experience integrating AI solutions with APIs databases and enterprise platforms.

Nice to Have

• Experience with Azure AI services.
• Experience with Databricks.
• Experience in Financial Services Insurance AML KYC Fraud Prevention or other regulated industries.

Additional Information :

Benefits:

Full access to foreign language learning platform

Personalized access to tech learning platforms

Tailored workshops and trainings to sustain your growth

Medical Insurance

Meal tickets

Monthly budget to allocate on flexible benefit platform

Access to 7 Card services

Wellbeing activities and gatherings

Remote Work :

Yes

Employment Type :

Full-time