Note: The job is a remote job and is open to candidates in USA. Aimpoint Digital is a market-leading data, AI, analytics, and operations research advisory and solution engineering firm. As a Senior AI Engineer, you will work directly with clients to design, build, deploy, and scale enterprise AI solutions, combining strong software engineering fundamentals with modern AI technologies to deliver production-ready systems that create measurable business value.
Responsibilities
- 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
Skills
- 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
- 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
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