As a Senior AI Engineer, you will work directly with clients to design, build, deploy, and scale enterprise AI solutions. You will combine strong software engineering fundamentals with modern AI technologies to deliver production-ready systems that create measurable business value.
You will work across the entire AI engineering lifecycle; from solution architecture and application development to deployment, evaluation, and operationalization.
What You Will Do
Design, build, and deploy production AI applications, copilots, retrieval systems, and agentic workflows
Translate business problems into scalable technical solutions using modern AI engineering best practices
Develop backend services, APIs, and application architectures that integrate AI capabilities into enterprise systems
Build multi-agent systems, AI agents, workflow automation, and decision-support systems
Deploy AI solutions into production with appropriate security, observability, monitoring, evaluation, and governance
Design AI systems that integrate with enterprise data platforms, APIs, databases, messaging systems, and business applications
Collaborate with cross-functional client teams including engineering, data, product, architecture, security, and business stakeholders
Experience deploying and operating containerized applications on Kubernetes, including scaling, service networking, resource management, and production monitoring
Contribute reusable accelerators, frameworks, technical assets, and thought leadership that strengthen the AI Engineering practice
Stay current with emerging AI technologies and recommend practical approaches that improve client outcomes
Qualifications
Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent practical experience
3+ years of professional software engineering experience building production applications
1+ years designing and deploying AI or machine learning solutions into production
Strong programming experience using Python, Java, C#, Go, TypeScript, or similar languages
Experience building scalable backend systems, APIs, or distributed applications
Experience developing AI applications using modern LLMs, machine learning models, or intelligent automation solutions
Experience with online and offline evaluation, observability, context engineering, guardrails, and AI governance
Experience with MLOps, LLMOps, or production deployment pipelines
Strong understanding of software engineering principles, including testing, version control, CI/CD, code reviews, and system design
Experience using Claude Code, OpenAI Codex, Google Antigravity, Cursor, GitHub Copilot, or other comparable coding harnesses
Experience integrating AI applications with enterprise data sources, APIs, and business systems
Familiarity with cloud platforms such as AWS, Azure, GCP, Databricks, Snowflake, or similar technologies
Experience deploying applications using containers, Kubernetes, serverless platforms, or similar cloud-native technologies
Strong communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders
Ability to independently own technical workstreams while collaborating across multidisciplinary teams
Preferred Qualifications
Experience developing production APIs using frameworks such as FastAPI, Flask, Spring Boot, .NET, and Express
Experience building multi-agent systems, AI automated workflows, agents, semantic search, vector databases, or knowledge graph retrieval applications
Experience designing distributed systems, concurrency, or high-scale cloud applications
Experience deploying AI solutions serving 1000+ users
Consulting experience or experience working directly with enterprise customers
Experience building data pipelines, including ETL, ELT, batch, and streaming pipelines for analytics and AI applications
Experience pre-training or fine-tuning LLMs
Company Description
Aimpoint Digital is a market-leading data, AI, analytics, and operations research advisory and solution engineering firm. We help organizations design, build, and operationalize enterprise-grade data and AI platforms, decision intelligence solutions, optimization systems, and production AI applications.
We are not a commodity consulting firm. We are a technical partner to organizations that need to move beyond experimentation and deploy AI into real business workflows with the architecture, governance, reliability, and engineering discipline required for production.
We believe successful AI initiatives require much more than prompting an LLM. They require strong software engineering, scalable architecture, reliable deployment, thoughtful evaluation, and disciplined engineering practices.