Forward Deployed AI Engineer, Java Experience

This is a fully remote position, open to applicants in Argentina.

📋 Description

• Develop production services using Java — design and implement microservices (Spring Boot) that connect customer systems with our platform and AI capabilities.

• Engineer AI-driven functionalities — create LLM/GenAI applications utilizing model APIs (Anthropic Claude, OpenAI, AWS Bedrock, etc.): RAG pipelines, agentic workflows, tool/function calling, prompt engineering, and evaluation.

• Deploy and manage in the cloud — construct, ship, and operate services and AI workloads on AWS, containerized and orchestrated with Kubernetes.

• Collaborate with customers/partners — engage directly with client teams to gather requirements, design AI solutions, and guide them to implementation — including responsibly managing expectations regarding the capabilities and limitations of AI.

• Take ownership of the complete lifecycle — from discovery, design, implementation, evaluation, deployment, to post-launch support of both services and AI features.

• Prepare AI for production — tackle complex issues: grounding/hallucination control, latency and cost optimization, guardrails, observability, and the evaluation/testing of non-deterministic systems.

• Troubleshoot across the stack — identify issues that span distributed systems, APIs, data pipelines, model integrations, and infrastructure.

• Convert ambiguity into architecture — transform loosely-defined business requirements into clear technical designs; advocate for better or safer approaches when necessary.

• Enhance the platform — integrate field insights back into the product; develop reusable AI patterns, tools, prompts, and documentation.

⛳️ Requirements

• A minimum of 3 years of professional software engineering experience with a strong command of Java (Java 8–21).

• Practical experience with Spring Boot and building/consuming RESTful APIs.

• Experience in applied AI/LLM engineering — you have built and delivered real solutions with LLMs: e.g. RAG, agents, tool calling, prompt engineering, or model-API integration (Claude, OpenAI, Bedrock, Gemini, or similar).

• Familiarity with AWS — deploying and running applications using core services (EC2, S3, IAM, RDS, Lambda, CloudWatch); knowledge of AWS AI/ML services (e.g. Bedrock, SageMaker) is a significant advantage.

• Exposure to Kubernetes — deploying, managing, and troubleshooting containerized workloads (Docker + K8s).

• Strong understanding of relational databases (SQL); knowledge of vector databases/embeddings for retrieval is a plus.

• Excellent debugging and problem-solving skills in distributed and AI-integrated systems.

• Strong communication skills — comfortable interacting directly with customers and non-technical stakeholders, including articulating AI capabilities and limitations.

• Bachelor's degree in Computer Science or equivalent practical experience.

🏝️ Benefits

• Flexible working hours and options for remote work.

• Opportunities for professional growth and development.

• A collaborative and inclusive work environment.

• The opportunity to engage in impactful projects with a talented team.

• Competitive compensation in USD.

• Hardware and software setup provided.