Senior GenAl Engineer
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Job Location:
Monthly Salary:
Posted on:
18 hours ago
Vacancies:
1 Vacancy
Job Summary
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 todays 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
- Bachelors 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
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
Key Skills
- APIs
- C/C++
- Computer Graphics
- Go
- React
- Redux
- Node.js
- AWS
- Library Services
- Assembly
- GraphQL
- High Voltage
