
Forward Deployed AI Engineer
Posted 4 days ago

Posted 4 days ago
This is a fully remote position, open to applicants in United States, +2 more countries.
• Engage directly with clients to architect, construct, implement, and scale enterprise AI solutions.
• Create, implement, and launch production-ready AI applications, copilots, retrieval systems, and automated workflows.
• Convert business challenges into scalable technical solutions utilizing contemporary AI engineering methodologies.
• Design backend services, APIs, and application architectures to integrate AI functionalities into enterprise systems.
• Develop multi-agent systems, AI agents, automation workflows, and decision-support systems.
• Implement AI solutions in production with an emphasis on security, observability, monitoring, evaluation, and governance.
• Create AI systems that integrate seamlessly with enterprise data platforms, APIs, databases, messaging systems, and business applications.
• Collaborate effectively with engineering, data, product, architecture, security, and business stakeholders.
• Deploy and manage containerized applications on Kubernetes, focusing on scaling, service networking, resource management, and production monitoring.
• Contribute reusable accelerators, frameworks, technical assets, and thought leadership to the AI Engineering discipline.
• Keep abreast of emerging AI technologies and propose strategies that enhance client outcomes.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related practical field.
• Over 3 years of professional software engineering experience in developing production applications.
• At least 1 year of experience in designing and deploying AI or machine learning solutions in production settings.
• Proficient in programming languages such as Python, Java, C#, Go, TypeScript, or similar.
• Experience in building scalable backend systems, APIs, or distributed applications.
• Skilled in developing AI applications utilizing modern LLMs, machine learning models, or intelligent automation solutions.
• Familiarity with online and offline evaluation, observability, context engineering, guardrails, and AI governance.
• Knowledge of MLOps, LLMOps, or production deployment pipelines.
• Strong grasp of software engineering principles, including testing, version control, CI/CD, code reviews, and system design.
• Experience using tools like Claude Code, OpenAI Codex, Google Antigravity, Cursor, GitHub Copilot, or similar coding platforms.
• Proven experience in integrating AI applications with enterprise data sources, APIs, and business systems.
• Familiarity with cloud platforms like AWS, Azure, GCP, Databricks, Snowflake, or similar technologies.
• Experience deploying applications using containers, Kubernetes, serverless platforms, or other cloud-native solutions.
• Excellent communication skills with both technical and non-technical stakeholders.
• Capability to independently manage technical workstreams while collaborating across diverse teams.
• Preferred: experience with production APIs using FastAPI, Flask, Spring Boot, .NET, or Express.
• Preferred: familiarity with multi-agent systems, AI automated workflows, agents, semantic search, vector databases, or knowledge graph retrieval applications.
• Preferred: experience in distributed systems, concurrency, or high-scale cloud applications.
• Preferred: AI solutions catering to 1000+ users.
• Preferred: consulting experience or direct engagement with enterprise customers.
• Preferred: expertise in data pipelines, including ETL, ELT, batch, and streaming pipelines.
• Preferred: experience in pre-training or fine-tuning LLMs.
• Full-time employment.
• Remote work opportunities available within the US, Colombia, and the UK.
• Applicants in Atlanta may have the option to work at headquarters located in Sandy Springs, Georgia.
Alzheimer's Association®
Capital One
Capital One
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