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 integral 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.

📌 Senior Software Engineer (Colombia)
🏢 CaseWare
📍 Colombia