Forward Deployed Engineer AI Solutions

Brainwaves Digital is looking for a highly committed, hands-on Forward Deployed Engineer to work at the intersection of customer business problems, applied AI, software engineering, data, automation, and digital solution delivery.

This is a builder role for someone who can work directly with clients, understand business situations, rapidly learn new domains, and convert problems into working technical solutions. The role requires a strong technical mindset, practical problem-solving ability, and the hunger to learn bleeding-edge technologies quickly.

Experience is helpful, but not mandatory. We care more about ownership, learning speed, technical curiosity, commitment, and a solutions-first attitude. The right person should be comfortable using AI tools, LLMs, coding assistants, modern engineering workflows, and hands-on experimentation to move fast.

This role is ideal for someone who wants to grow long term with Brainwaves Digital and become a deeply capable, customer-facing technologist.

What You Will Do

· Work directly with clients to understand business goals, workflows, pain points, systems, data, and operating constraints.

· Translate ambiguous business problems into clear solution designs, prototypes, demos, implementation plans, and technical delivery tasks.

· Build practical AI, automation, data, workflow, application, and integration solutions for real customer use cases.

· Use LLMs and AI-assisted development tools to accelerate coding, debugging, documentation, research, workflow design, and solution prototyping.

· Develop and support solution components using modern tools such as Python, TypeScript, APIs, databases, Docker, Linux environments, and cloud or container-based services.

· Work with frontend and backend workflows, including TypeScript, npm-based tooling, APIs, services, integrations, and user-facing solution components.

· Learn and work across advanced engineering areas such as Rust, WASM, data pipelines, vector databases, graph databases, and AI-enabled applications.

· Support environments involving Docker, CI/CD workflows, artifact handling, deployment coordination, testing, and release readiness.

· Explore and prototype with data and AI tools, including Jupyter notebooks, retrieval workflows, embeddings, knowledge graphs, and LLM-powered applications.

· Troubleshoot issues across applications, data flows, integrations, APIs, environments, containers, prompts, pipelines, and user workflows.

· Create client-facing and internal artifacts, including demos, proof-of-concepts, technical notes, process maps, solution designs, implementation documentation, and walkthrough materials.

· Own outcomes from discovery through prototype, pilot, deployment, adoption, feedback, and measurable business improvement.

Technical Areas You May Work Across

You do not need to know everything on day one, but you must be excited and able to learn quickly across areas such as:

· APIs, integrations, services, data exchange, and application connectivity.

· Linux, Docker, containers, development environments, and troubleshooting.

· CI/CD workflows, build systems, artifact handling, release processes, and environment reliability.

· Rust, WASM, and modern high-performance application components.

· LLMs, AI agents, prompt engineering, retrieval-augmented generation, embeddings, and AI-assisted engineering.

· Databases and services such as MongoDB, Redis, Qdrant, Neo4j, TerminusDB, and similar platforms.

· Jupyter, notebooks, data exploration, analytics, dashboards, and reporting workflows.

· Cloud platforms, deployment environments, security basics, credential handling, and production-readiness practices.

Required Qualifications

· Strong technical aptitude and genuine interest in building working solutions.

· Ability to learn new technologies, business domains, customer workflows, and technical stacks quickly.

· Hands-on exposure to at least some of the following: Python, JavaScript, TypeScript, SQL, APIs, databases, Docker, Linux, cloud platforms, AI tools, or automation frameworks.

· Comfort using LLMs, AI coding assistants, and modern developer tools to accelerate engineering work.

· Strong debugging and troubleshooting mindset across code, data, systems, integrations, and user workflows.

· Ability to communicate clearly with business users, technical teams, and leadership.

· Willingness to work directly with customers, ask good questions, and understand the business outco…