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Medellín, Antioquia, Colombia
Remote only
Create architecture, prototypes, and design proposals that deliver near-term business value while aligning with the future-state product and platform vision.
Influence technical direction through architecture reviews, RFCs, design discussions, and hands-on collaboration.
Partner with senior developers, architects, and tech leads to define and execute the product/platform architecture roadmap.
Balance delivery speed, quality, maintainability, and long-term platform health when making technical decisions.
Break down large initiatives into parallelizable chunks of work that deliver incremental business value.
Champion proposals through all phases of the SDLC, from design through production implementation.
Contribute to improving the core product build, CI/CD pipelines, and overall SDLC.
Troubleshoot and eliminate root causes of persistent production issues; drive reliability, observability, monitoring, and incident response.
Keep technical documentation current and create new artifacts as needed.
Facilitate design discussions within and across teams.
Represent the team in technical discussions with Tech Leads, Operations, Product/UX, Security, Domain SMEs, and external stakeholders.
Act as a trusted technical leader, helping teams succeed through collaboration, influence, and shared ownership.
Mentor other developers through design reviews, joint agentic-AI sessions, and feedback on skills, prompts, and other agent inputs; contribute to raising overall engineering maturity.
Share knowledge of new technologies and industry best practices.
Evaluate emerging technologies, frameworks, and cloud capabilities that could benefit the platform.
Use AI-assisted development tools — inline completion, conversational assistants, and agentic workflows — as a standard part of your daily workflow.
Critically evaluate and take ownership of all AI-generated output before it ships — verify correctness, security, and alignment with architecture and team standards.
Identify opportunities for agentic automation within your team, and lead the rollout of new AI-assisted workflows and tooling.
Mentor other developers on effective, responsible use of AI-assisted development tools.
Help establish team-level practices and guardrails for using AI tools safely and effectively.
Build and refine feedback loops that improve the team's collective use of AI tooling over time.
Degree in Computer Science, Software Engineering, or equivalent practical experience; 8+ years of professional software development experience with demonstrated impact beyond a single team.
Proven experience designing and operating distributed, cloud-native, SaaS/multi-tenant platforms at scale, ideally on AWS.
Strong software fundamentals: OOP, design patterns, SOLID principles, and a track record of advocating for code quality.
Experience with agentic-AI software development practices.
Experience designing and consuming well-designed HTTP APIs (REST, GraphQL, or similar).
Experience mentoring developers and influencing architectural decisions across teams.
Strong written and verbal communication skills; comfortable operating in fast-moving environments with ambiguity and evolving requirements. English high B2.
Strong initiative to improve processes, tools, methodologies, and product quality.
Build and operate the AWS AgentCore Gateway layer and the capabilities it hosts — MCP tool targets today, extending to inbound access, agent-to-agent (HTTP) targets, and inference/model-routing targets as those capabilities come online.
Develop and maintain the target registry and configuration model that lets customer firms register their own MCP servers for their agents to call, covering tenant isolation, credential handling, allowlisting and egress control, and containment when a third-party endpoint fails or misbehaves.
Build the inbound surface that exposes Caseware capability to external agents and clients over MCP and adjacent protocols, including authentication, scope enforcement, and rate limiting.
Build and operate the on-premise connectivity path, including session lifecycle, request correlation, and recovery for long-lived sessions between cloud-hosted agents and on-premise desktop clients.
Implement session and scope propagation from agent to gateway to target to backend, so authorization is correct and auditable at every hop.
Design and evolve OpenAPI contracts for gateway targets, and the target runtimes that implement them, keeping conventions consistent regardless of what a target fronts.
Implement outbound authorization for gateway targets (IAM/SigV4, OAuth, credential providers) so access to each target type is securely and consistently controlled.
Maintain versioning of target contracts as they evolve, so consuming teams and customers are not broken by change.
Contribute to end-to-end tracing and SLOs for gateway traffic, and build the observability that lets you and other teams detect and debug failures anywhere in the pipeline.
Mentor other developers joining the team, and contribute to technical direction for the integration layer through RFCs and design reviews.
Experience with MCP (Model Context Protocol) for LLM agents.
Experience building or operating a multi-tenant gateway or API platform: several traffic patterns behind one access point, tenant isolation, per-tenant credentials and secrets, quotas, and abuse protection.
Experience integrating with third-party or untrusted endpoints, with a clear point of view on failure containment and limiting blast radius.
Experience with authorization and scope propagation across multi-hop service boundaries — carrying and checking identity and permissions through the full pipeline, not just authenticating once.
Experience designing and operating persistent-connection or streaming architectures, including session management, recovery, and message correlation, along with related protocol-level concerns (timeout/retry semantics, backpressure, idempotency, graceful degradation).
Experience with AWS Bedrock, AgentCore, or other managed agent/LLM orchestration platforms.
Experience with LLM provider routing and gateway patterns (multi-provider endpoints, model-based routing) or agent-to-agent (A2A) communication protocols.
Experience building developer- or partner-facing platform surfaces that external parties integrate against.
Experience integrating cloud services with on-premise or embedded clients (webviews, desktop apps).
Familiarity with Infrastructure as Code (CDK, CloudFormation, or Terraform).
Experience operating systems in regulated or compliance-heavy domains.
Backend & Platform: Node.js/TypeScript
Cloud & Infrastructure: AWS Lambda, AWS Bedrock, AWS AgentCore Gateway (or similar third-party platforms/tools)
Connectivity: Persistent-connection relay architecture for on-premise integrations
Contracts & Protocols: OpenAPI, Model Context Protocol (MCP), A2UI
Developer Tooling: GitHub, GitHub Actions