Senior Software Developer III

As a Senior Software Developer III, you operate as a technical leader within your team and across the broader engineering organization. You shape architecture and design, raise the bar on engineering quality, mentor other developers, and partner closely with cross-functional stakeholders to translate technical decisions into business value. You are equally comfortable guiding agentic-AI tools to deliver code, reviewing designs, and influencing how the platform evolves.

Location: This is a fully remote position located in Colombia.

Contact

Maira Russo - Senior Talent Acquisition Partner

What You’ll Be Doing:

• You build it, you run it. End-to-end accountability for the AI platform in production: architecture, delivery, operations, cost, and quality, with on-call for what you ship. No hand-off to a separate ops or QA function.

• Design, build, and operate agentic AI systems: LLM services, retrieval pipelines, multi-agent orchestration, agent execution runtimes, and human-in-the-loop capabilities.

• Build and operate memory infrastructure for agent systems (storage, retrieval, promotion/demotion mechanics). Applied Science owns promotion criteria and scientific soundness.

• Own LLMOps: the harnesses, pipelines, and infrastructure that keep non-deterministic systems reliable and correct in production, including dynamic model selection by task, cost, and latency.

• Build automated eval infrastructure that continuously compares offline and online metrics and alerts on drift or regression. Applied Science owns the methodology and acceptance thresholds it checks against.

• Evaluate, adopt, and integrate third-party LLMOps and eval platforms where they accelerate delivery over building in-house.

• Build the technical controls, telemetry, and guardrails that enforce compliance frameworks (e.g., ISO 42001, AIUC-1) in the architecture itself.

• Build and maintain the agent definition management APIs and the tool registry definitions reference, keeping definitions stable as tools and models version independently.

• Lead the engineering build of proof-of-concepts. Applied Science defines the architecture bet and validation criteria being tested.

Core Responsibilities

• 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.

AI-Augmented Development Expectations:

• 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.

What You Will Bring:

• 2+ years building and operating production AI systems, with a working grasp of the latency, cost, accuracy, and reliability trade-offs involved.

• Experience with agent frameworks, agent memory systems, or orchestration of tool-using AI systems.

• Production AWS experience, including Infrastructure as Code (CDK, CloudFormation, or Terraform).

• 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.

• Strong initiative to improve processes, tools, methodologies, and product quality.

Nice to Have

• Experience implementing AI guardrails, governance controls, and safety mechanisms, and translating compliance frameworks (e.g., ISO 42001, AIUC-1, NIST AI RMF) into technical controls.

• Experience evaluating and integrating third-party ML/LLMOps platforms, with sound buy vs. build judgment.

• Experience with retrieval systems (RAG), embedding pipelines, or hybrid search (vector + keyword).

• LLMOps experience: evaluation harnesses, automated offline/online metric comparison, drift and regression alerting.

• Experience operating systems in regulated or compliance-heavy domains.

• Familiarity with accounting, auditing, or financial workflows.

Tech Stack

• Reliability & Observability: New Relic, CloudWatch, Prometheus, OpenTelemetry or equivalent

• Cloud & Infrastructure: AWS, EKS, Lambda, S3, DynamoDB, IAM, VPC

• Containers & Orchestration: Docker, Kubernetes

• Automation & Scripting: Python, Bash, TypeScript or equivalent

• Incident & Operations: runbooks, alerting workflows, incident management tools, post-incident review practices

• Tooling: GitHub, GitHub Actions, Jira, Confluence, Microsoft Teams, Slack

Perks & Benefits

• ¨Contrato a termino Indefinido¨ with all the legal benefits
• Prepaid Medicine
• Life insurance and funeral assistance
• Internet allowance
• Home office stipend
• Competitive compensation - above the market average
• 100% remote work environment and an excellent work-life balance
• 5 Personal Time Off days per year
• Sick Leave Top up to total 100% of salary paid by the employer from Day 3 to 90.
• Recognition Award, additional paid time off in recognition of the corresponding year of service
• Upgrade vacation starting at 5 years of service
• Opportunity to work for a growing global SaaS leader company
• A culture that promotes independence, innovation, trust, and accountability
• Open space to be creative, innovative and strategize for the future
• Mentorship by highly experienced professional
• Budget for training, we want you to grow
• AI-first environment: Be part of an AI-first engineering organization that embraces modern tools, automation, and AI-driven ways of working.