Senior GenAl Engineer

What were looking for Senior GenAl Engineer
(Only for people located in Latinamerica).
Our client leads the way in AI innovation, leveraging cutting-edge technology to transform legacy systems into modern, efficient, and scalable solutions. They work with enterprise clients to future-proof their applications, helping them meet the demands of today's dynamic digital environment. The team excels at solving complex challenges and delivering AI-powered solutions. They foster a culture of creativity, collaboration, and continuous learning
.
We are seeking a highly skilled
Senior GenAl Engineer (Multi-Agent Systems)
to play a key role in advancing our Al-driven platform and client solutions.

The ideal candidate has 4+ years of hands-on Machine Learning (ML) experience beyond academia, thrives in fast-paced environments, and enjoys solving complex technical challenges. A strong foundation in cloud-based ML solutions, Al model deployment, and optimization techniques is essential. Those with a passion for staying at the forefront of Al advancements and delivering high impact solutions will excel in this role.

Key Responsibilities:

• Architect and scale multi-agent orchestration frameworks (e.g., LangGraph, AutoGen, Llamalndex, CrewAl)
• Implement agent-to-agent communication, memory and state management Build evaluation and feedback loops (e.g., latency, success-rate, hallucination control, cost)
• Integrate agents with external APIs, data systems and event streams Ensure scalability, observability and MLOps for agent workflows
• Contribute to building and enhancing our Mechanized Al platform and mAln Modernize product suite
• Serve as ML SME on client projects, as needed
• Design ML systems
• Research and implement appropriate ML algorithms and tools
• Select appropriate datasets and data representation methods
• Run ML tests and experiments
• Extend existing ML libraries and frameworks
• Stay current with emerging technologies and ML best practices to continuously improve our methodologies and tools

Experience And Knowledge

• 5+ years of professional software (Al preferred) engineering
• 2+ years building production LLM or multi-agent systems
• Practical proficiency with graph databases (e.g., TigerGraph, Neo4j) and graph-based retrieval (e.g., GraphRAG), plus experience with vector databases like Opensearch, CosmosDB, or Pinecone
• Deep experience with one or more: LangGraph, AutoGen 0.4, Llamalndex
• AgentWorkflow, ag2, strands agents, etc
• Retrieval for agents: Opensearch plus TigerGraph and GraphRAG patterns for global reasoning
• Observability: Langfuse or Phoenix with OpenTelemetry; track quality, cost, and latency
• Serving: Deploy and scale agentic workloads via AWS Fargate, Step Functions, and Lambdas (or equivalent services on other clouds), ensuring p95 latency targets
• Safety by design aligned to OWASP LLM Top 10; implement policy-compliant tool scopes and output validation.
• Interoperability: Model Context Protocol (MCP) for tool and data access, with bonus for LangGraph MCP adapters
• Experience with cloud environments (e.g., AWS, Azure, GCP): ECS, Step Functions, Lambda and equivalents on other clouds.
• Experience developing, deploying, and managing/monitoring non-open source LLMs
• Knowledge of containerization technologies (e.g., Docker, Kubernetes) and microservices architecture
• Expertise in Object-Oriented Programming (OOP) principles and unit test-driven development methodologies
• Retrieval-augmented generation (RAG) optimization
• Advanced experience in NLP techniques and applications
• Strong proficiency in Python programming
• Familiarity with prompt engineering approaches and best practices
• Knowledge of data structures, data modeling, and software architecture
• Bachelor's degree in computer science, software engineering or related field
• Strong analytical and problem-solving skills, with ability to propose innovative solutions and troubleshoot issues
• Ability to work independently and as part of a collaborative team in a fast-paced environment
• English B2
• Only for people located in Latinamerica

Preferred Qualifications:

• Agent development
• Data privacy
• Fine tuning LLMs
• -LM architecture and techniques for performance
• LLMOps
• MLevaluation
• Model decay and data drift detection and handling
• lac: Pulumi, Terraform, and/or Cloud SDKs
• Security
• Vector databases

Compensation & Benefits

• Participation in innovative, high-impact regional projects.
• People-centric culture with autonomy and continuous learning.
• Work 100% Remote
• Work from anywhere
• We pay in US dollars.
• 40 USD BYOD.
• You can enjoy all the holidays in your country.
• 10 days of PTO payments