Job description

About us Appnovation is the AI Product Company. Headquartered in Vancouver, Canada, with teams around the world, Appnovation builds AI products, delivers enterprise AI and digital solutions, and co-invests with clients to bring new AI products to market. Open source has been the foundation of Appnovation's work since 2007, and it remains the foundation underneath every AI product the company builds today. Appnovation teams work with organizations in highly regulated industries, including global leaders such as Pfizer, Google and AstraZeneca, to help them adopt AI they can govern and own. We’re hiring AgentCore Platform Engineers to build the agent-facing layer of the platform. That covers how agents run, remember and work together, and how they safely reach the internal systems the business already runs on. Each engineer will have a main focus in one of the two areas below and work closely across both. What you build becomes the template other teams copy, so quality and clarity matter as much as speed. This is a named-team engagement, so the person we propose is the person who starts. We know production experience with Bedrock AgentCore is rare. We care more about strong AWS fundamentals and real hands-on work with agent frameworks than about whether you’ve used AgentCore by name. If that’s you, please apply. FOCUS AREAS Agent Runtime & Orchestration: Build runtime patterns, memory strategies, orchestration and multi-agent handoffs, and the reference implementations other teams copy. Gateway, Tools & Integrations: Turn internal APIs, Lambdas and legacy systems into governed tools through AgentCore Gateway, including MCP server development. ROLE RESPONSIBILITIES Runtime Patterns: Define how agents are structured, packaged and run on AgentCore Runtime, including sessions, state, error handling and timeouts. Memory Strategies: Design short-term and long-term memory patterns using AgentCore Memory, and guide teams on when to use which. Orchestration and Multi-Agent Handoffs: Build patterns for planning, tool use, supervisor/worker setups and handoffs between agents, with clear boundaries and fallbacks. Tool Onboarding: Expose internal REST APIs, Lambda functions and legacy services as agent tools through AgentCore Gateway, using OpenAPI specs and Lambda targets. MCP Server Development: Design and build Model Context Protocol (MCP) servers for systems that need custom integration, with clean tool definitions and schemas. Governance and Access: Set up authentication and authorization for agents and tools (AgentCore Identity, OAuth, IAM) so agents only reach what they’re allowed to. Legacy Integration: Work with system owners to wrap older or on-premises systems safely, handling rate limits, data mapping and error cases. Reference Implementations and Standards: Build production-quality reference agents, starter kits and a repeatable process for adding, versioning and reviewing tools. Evaluation and Guardrails: Build in evaluation, Bedrock Guardrails, contract tests and safety checks so agents and tools behave predictably before going live. Enablement: Run walkthroughs, write docs and support the teams onboarding to the platform. QUALIFICATIONS 5+ years of software engineering experience, with strong Python (TypeScript is a plus). Hands-on experience building LLM agents with at least one agent framework (e.g., Strands Agents, LangGraph, LangChain, CrewAI, OpenAI Agents SDK, LlamaIndex). Practical experience with LLM tool/function calling and handling model output. Strong AWS fundamentals: IAM, Lambda, API Gateway, containers, DynamoDB/S3, VPC connectivity and Secrets Manager. Experience designing and consuming REST APIs and OpenAPI specs, and auth patterns such as OAuth 2.0 and OIDC. Understanding of agent memory, retrieval (RAG) and context management trade-offs. Deep hands-on strength in at least one of the two focus areas, and working knowledge of the other. Clean, well-tested code that other engineers will read and reuse. Clear communication and comfortable teaching patterns to other teams. PREFERRED QUALIFICATIONS Hands-on experience with Amazon Bedrock AgentCore (Runtime, Memory, Gateway, Identity). A strong plus, but not required. Experience building or running MCP servers in a real environment. Experience with multi-agent systems in production, including observability and failure handling. Experience integrating with enterprise or legacy systems, or with API management platforms (e.g., MuleSoft, Apigee, Kong). Experience with LLM evaluation tools and approaches. Experience in pharma, life sciences or another regulated industry with data access controls. WHO YOU ARE You’ve built agents that actually work, and you know where they tend to break You care about patterns other people can copy, not just clever one-offs You think about security and access control before anything goes live You pick up new AWS services quickly and learn by building You’re honest about what agents can and can’t do today You work well inside a client team and enjoy helping other engineers succeed You have prior experience in consulting Prior experience and connections in the Life Sciences industry is preferred Thank you for your interest in a career with Appnovation Technologies! Please note that only those selected for an interview will be contacted. At Appnovation, we recognize that diverse teams are the strongest teams. Diversity, Equity & Inclusion is not only something that we embrace - we celebrate it! We are proud to be an Equal Opportunity Employer and we encourage applicants from all backgrounds, lived experiences and industries to apply. Come join us at Appnovation, and learn more about how we stay true to our company values as we build better lives through better digital. Accommodations are available upon request throughout the recruitment process.

Requirements

Must-haves

Agent Runtime & Orchestration: Build runtime patterns, memory strategies, orchestration and multi-agent handoffs, and the reference implementations other teams copy.
Gateway, Tools & Integrations: Turn internal APIs, Lambdas and legacy systems into governed tools through AgentCore Gateway, including MCP server development.
Runtime Patterns: Define how agents are structured, packaged and run on AgentCore Runtime, including sessions, state, error handling and timeouts.
Memory Strategies: Design short-term and long-term memory patterns using AgentCore Memory, and guide teams on when to use which.
Orchestration and Multi-Agent Handoffs: Build patterns for planning, tool use, supervisor/worker setups and handoffs between agents, with clear boundaries and fallbacks.
Tool Onboarding: Expose internal REST APIs, Lambda functions and legacy services as agent tools through AgentCore Gateway, using OpenAPI specs and Lambda targets.
MCP Server Development: Design and build Model Context Protocol (MCP) servers for systems that need custom integration, with clean tool definitions and schemas.
Governance and Access: Set up authentication and authorization for agents and tools (AgentCore Identity, OAuth, IAM) so agents only reach what they’re allowed to.
Legacy Integration: Work with system owners to wrap older or on-premises systems safely, handling rate limits, data mapping and error cases.
Reference Implementations and Standards: Build production-quality reference agents, starter kits and a repeatable process for adding, versioning and reviewing tools.
Evaluation and Guardrails: Build in evaluation, Bedrock Guardrails, contract tests and safety checks so agents and tools behave predictably before going live.
Enablement: Run walkthroughs, write docs and support the teams onboarding to the platform.
Hands-on experience building LLM agents with at least one agent framework (e.g., Strands Agents, LangGraph, LangChain, CrewAI, OpenAI Agents SDK, LlamaIndex).
Practical experience with LLM tool/function calling and handling model output.
Strong AWS fundamentals: IAM, Lambda, API Gateway, containers, DynamoDB/S3, VPC connectivity and Secrets Manager.
Experience designing and consuming REST APIs and OpenAPI specs, and auth patterns such as OAuth 2.0 and OIDC.
Understanding of agent memory, retrieval (RAG) and context management trade-offs.

Nice-to-haves

5+ years of software engineering experience, with strong Python (TypeScript is a plus).
Experience building or running MCP servers in a real environment.
Experience with multi-agent systems in production, including observability and failure handling.
Experience integrating with enterprise or legacy systems, or with API management platforms (e.g., MuleSoft, Apigee, Kong).
Experience with LLM evaluation tools and approaches.
Experience in pharma, life sciences or another regulated industry with data access controls.
Prior experience and connections in the Life Sciences industry is preferred

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiawsrestpythontypescriptllmapi

Platform: greenhouse
Effort: quick