Senior AI Platform Engineer with LangGrap
DataArt
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Benefits offered by this job
Job summary
Aether Biomedical seeks a Senior AI Platform Engineer to advance a scalable, agent-centric platform enabling intelligent agents to interact with enterprise tools and cloud environments. You will work on framework development, runtime integration, and observability for production-grade AI solutions.
The role emphasizes designing multi-agent orchestration, tool integration, and secure cloud deployments while collaborating with cross-functional teams to define standards and ensure reliability.
Qualifications
- 5+ years of professional Python engineering experience
- Production experience with LangGraph, Strands Agents, or a comparable agent orchestration framework
- Experience deploying and managing applications using AWS Bedrock or AWS Bedrock AgentCore Runtime
- Experience designing, developing, or contributing to internal agent frameworks, SDKs, or platform components
- Experience implementing multi agent coordination patterns including supervisor, swarm, delegation, or hierarchical approaches
- Strong understanding of agent architecture, orchestration, state management, and tool integration concepts
- Experience building cloud native applications and distributed systems on AWS
- Knowledge of software engineering best practices, testing strategies, and version control workflows
- Experience working with REST APIs, integration layers, and scalable backend services
Responsibilities
- Develop and enhance AI platform components, agent frameworks, and reusable SDK capabilities
- Design and implement multi agent orchestration patterns including ReAct, supervisor, hierarchical, and delegation based workflows
- Build integrations between agents, enterprise tools, and external services using MCP, A2A, and function calling approaches
- Develop solutions using LangGraph, including StateGraph, ToolNode, and create_react_agent patterns
- Implement and extend Strands Agents SDK components, including tool integrations and executor capabilities
- Deploy and manage agent workloads using AWS Bedrock AgentCore Runtime
- Design declarative configuration models using YAML driven Pydantic schemas
- Collaborate with platform and architecture teams to establish standards for agent execution and interoperability
- Implement observability capabilities using OpenTelemetry, AWS Distro for OpenTelemetry, AWS CloudWatch, and AWS X Ray
- Contribute to framework design, platform evolution, and engineering best practices
- Support troubleshooting, performance optimization, and operational reliability initiatives
Skills
Tools
Job description
Python, LangGraph, Strands Agents SDK, AWS Bedrock AgentCore Runtime, AWS, MCP, A2A, LangChain MCP Adapters, AWS Signature Version 4, Pydantic, YAML, OpenTelemetry, AWS Distro for OpenTelemetry, AWS CloudWatch, AWS X Ray, Git, CI/CD
The project focuses on building a configurable multi agent platform that supports autonomous workflows, agent collaboration, tool integration, and governed execution. The platform leverages modern agent orchestration frameworks, cloud native services, and observability solutions to deliver reliable and scalable AI capabilities across enterprise environments.
Medium team (10-20 people)You will work within a cross functional team of AI engineers, platform engineers, software developers, solution architects, and cloud specialists. The team collaborates closely on architecture decisions, framework development, platform capabilities, and operational excellence to support enterprise AI initiatives.
We are looking for a Senior AI Platform Engineer with strong experience in agentic AI systems, multi agent orchestration, and Python engineering. You will contribute to the design and development of a scalable AI platform that enables intelligent agents to collaborate, interact with enterprise tools, and operate within secure cloud environments. The role combines framework development, platform engineering, runtime integration, and observability for production grade AI solutions.
- Develop and enhance AI platform components, agent frameworks, and reusable SDK capabilities
- Design and implement multi agent orchestration patterns including ReAct, supervisor, hierarchical, and delegation based workflows
- Build integrations between agents, enterprise tools, and external services using MCP, A2A, and function calling approaches
- Develop solutions using LangGraph, including StateGraph, ToolNode, and create_react_agent patterns
- Implement and extend Strands Agents SDK components, including tool integrations and executor capabilities
- Deploy and manage agent workloads using AWS Bedrock AgentCore Runtime
- Design declarative configuration models using YAML driven Pydantic schemas
- Collaborate with platform and architecture teams to establish standards for agent execution and interoperability
- Implement observability capabilities using OpenTelemetry, AWS Distro for OpenTelemetry, AWS CloudWatch, and AWS X Ray
- Contribute to framework design, platform evolution, and engineering best practices
- Support troubleshooting, performance optimization, and operational reliability initiatives
- 5+ years of professional Python engineering experience
- Production experience with LangGraph, Strands Agents, or a comparable agent orchestration framework
- Experience deploying and managing applications using AWS Bedrock or AWS Bedrock AgentCore Runtime
- Experience designing, developing, or contributing to internal agent frameworks, SDKs, or platform components
- Experience implementing multi agent coordination patterns including supervisor, swarm, delegation, or hierarchical approaches
- Strong understanding of agent architecture, orchestration, state management, and tool integration concepts
- Experience building cloud native applications and distributed systems on AWS
- Knowledge of software engineering best practices, testing strategies, and version control workflows
- Experience working with REST APIs, integration layers, and scalable backend services
- Experience working with both LangGraph and Strands as part of a dual framework strategy
- Knowledge of Bedrock AgentCore SDK internals and agentcore.json deployment configurations
- Experience with MCP and A2A protocol implementations
- Experience contributing to open source AI, LLM, or agent framework projects
- Experience implementing observability solutions using OpenTelemetry and AWS Distro for OpenTelemetry
- Familiarity with AWS CloudWatch, AWS X Ray, and AI workload monitoring
- Knowledge of enterprise AI platform architecture and governance practices
- Vacation days: Up to 26 business days per year.
- 10 illness/special days off per year (fully paid, no medical papers needed) for all contract types
- Health and life insurance (Luxmed)
- MyBenefit platform with Multisport option
- Internal psychological support service
- English language classes from the first working day
- Access to external learning platforms: O’Reilly, LinkedIn Learning, Udemy, and a wide catalog of diverse internal training
- Flexible workplace: work from the office, from home, or choose a hybrid option
- Tech Skills Mentoring Program
- Opportunities to develop as a public speaker, mentor, or technical interviewer
- Fully paid idle (bench) when not involved in a project
- Certification reimbursement (AWS, GCP, Microsoft, etc.)
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