Job Description - Forward-Deployed AI Engineer

Role focus: Hands-on AI-enabled solution delivery across multiple business use cases, combining software engineering, data integration, cloud deployment, stakeholder collaboration, and practical AI implementation.

About the Role

We are looking for a Forward-Deployed AI Engineer to help design, build, and operationalize AI-enabled solutions across multiple business use cases. This role will work closely with business stakeholders, product teams, data partners, and engineering teams to rapidly translate operational problems into working prototypes, production-ready applications, automations, and decision-support tools.

This is a hands-on individual contributor role. The right candidate will be comfortable working independently across a focused codebase, partnering with business users, understanding operational workflows, and shipping incremental improvements quickly. The role requires someone who can operate at the intersection of software engineering, AI-enabled solutioning, data integration, and business problem solving.

The engineer may support use cases such as fuel reconciliation, fuel integrity monitoring, exception detection, operational alerting, workflow automation, decision support, data quality improvement, and other AI-enabled business capabilities.

What You'll Be Working On

Building and enhancing AI-enabled tools and applications that support business operations, exception management, analytics, and workflow automation.

Developing backend services and APIs using Python, FastAPI, or similar frameworks to support web applications, data pipelines, AI workflows, and system integrations.

Creating lightweight front-end experiences using HTML, CSS, JavaScript, or similar technologies to enable business users to interact with data, alerts, recommendations, and operational insights.

Designing and implementing background processes that connect to databases, APIs, files, or enterprise data sources to detect anomalies, trigger workflows, generate insights, and support business decision-making.

Integrating AI capabilities such as large language models, retrieval-augmented generation, summarization, classification, natural language interfaces, assisted triage, and intelligent workflow automation.

Working with structured and unstructured data from multiple enterprise systems, including operational databases, cloud platforms, document repositories, APIs, and analytics environments.

Supporting authentication, authorization, and role-based access using enterprise identity platforms such as Microsoft Entra ID.

Deploying and supporting solutions in cloud environments, including AWS, Azure, or other approved enterprise platforms.

Building secure, maintainable, and observable applications using container platforms, secrets management, logging, monitoring, and deployment workflows.

Partnering with business stakeholders to understand pain points, validate prototypes, iterate based on feedback, and move high-value concepts toward production adoption.

Required Skills

Python, Backend, and API Development

3+ years of Python experience, with strong understanding of async/await, context managers, decorators, type hints, and modular application design.

Experience building APIs using FastAPI, Flask, Django, or similar Python web frameworks.

Strong understanding of REST APIs, HTTP concepts, status codes, cookies, sessions, redirects, and secure API patterns.

Experience designing backend services that support operational workflows, data processing, automation, and user-facing applications.

Ability to debug authentication flows, API integrations, background jobs, and production application issues.

Experience writing and maintaining automated tests using pytest or similar testing frameworks.

AI-Enabled Solution Development

Experience applying AI or machine learning capabilities to practical business problems.

Familiarity with large language models, prompt engineering, retrieval-augmented generation, semantic search, document processing, text classification, summarization, or natural language interfaces

Ability to evaluate where AI can add value and where deterministic rules, workflow logic, or traditional analytics are more appropriate.

Experience integrating AI services or model APIs into business applications, prototypes, or automation workflows.

Ability to design human-in-the-loop experiences where business users can review, validate, or act on AI-generated outputs.

Strong judgment in validating AI outputs, handling edge cases, and designing solutions that are transparent, explainable, and operationally useful.

SQL, Data, and Integration

Strong SQL skills, with the ability to write complex analytical queries against large operational datasets.

Experience working with relational databases such as Oracle, PostgreSQL, SQL Server, MySQL, or similar platforms.

Ability to connect to enterprise data sources, understand data models, and transform raw data into usable application logic or business insights.

Experience diagnosing query performance issues, reviewing execution plans, and optimizing data access patterns.

Familiarity with lightweight state persistence using SQLite or similar embedded databases.

Ability to work with APIs, flat files, cloud storage, and other integration patterns across enterprise systems.

Frontend and User Experience

Comfortable building simple, effective user interfaces using HTML, CSS, and JavaScript.

Ability to create business-facing screens for reviewing exceptions, alerts, recommendations, metrics, workflows, and operational status.

Experience with fetch APIs, DOM manipulation, form handling, tables, filters, and session-based user interactions.

Ability to work without heavy front-end frameworks when speed, simplicity, and maintainability are the priority.

Strong sense of usability, especially for internal tools used by operations, analysts, coordinators, or business leaders.

Cloud, Infrastructure, and DevOps

Experience deploying and supporting applications in cloud environments such as AWS, Azure, or similar platforms.

Familiarity with containerized application deployment using Docker and services such as ECS Fargate, Kubernetes, App Services, or equivalent platforms.

Experience with container registries, image builds, deployment updates, health checks, and troubleshooting startup failures.

Understanding of cloud networking basics, including load balancers, security groups, private subnets, NAT gateways, and environment configuration.

Experience with secrets management, environment variables, application logging, monitoring, and operational diagnostics.

Familiarity with IAM, task roles, execution roles, or similar least-privilege access patterns.

Security, Identity, and Enterprise Readiness

Familiarity with Microsoft Entra ID, Azure SSO, app registrations, redirect URIs, app roles, and user assignment.

Understanding of OAuth2 Authorization Code Flow and secure authentication patterns.

Experience supporting role-based access control for internal applications.

Awareness of enterprise security expectations, including least privilege, secure handling of credentials, data protection, auditability, and responsible AI considerations.

Good-to-Have Skills

AI-Assisted Development

Experience using GitHub Copilot, Microsoft Copilot, Claude, or similar tools to accelerate development, code review, debugging, test generation, and solution design.

Ability to use AI tools effectively while still validating outputs, understanding the codebase, and maintaining engineering ownership.

Comfort operating in an AI-augmented delivery model where rapid prototyping, critical review, and iterative refinement are part of the working style.

Microsoft and Enterprise Integration

Experience with Microsoft Graph API, especially for email, calendar, document, or workflow-related integrations.

Familiarity with SharePoint, Teams, OneDrive, Power Platform, or other Microsoft 365 services as enterprise data or workflow surfaces.

Experience integrating business workflows with shared mailboxes, notifications, approvals, or escalation processes.

Testing and Code Quality

Experience structuring test suites for async Python applications.

Familiarity with pytest-asyncio, httpx, test clients, mocks, and integration testing patterns.

Ability to write maintainable, readable code that can be handed over to other engineers or support teams.

Experience documenting technical decisions, deployment steps, troubleshooting guidance, and known limitations.

Soft Skills and Ways of Working

Comfortable working independently on ambiguous business problems with limited hand-holding.

Able to quickly understand business processes, operational pain points, and stakeholder needs.

Strong written and verbal communication skills, with the ability to document decisions, explain trade-offs, and summarize progress clearly.

Collaborative working style with business stakeholders, product owners, data teams, cloud/platform teams, and engineering partners.

Flexible and willing to learn new technologies, enterprise platforms, AI tools, and business domains as use cases evolve.

Bias toward practical delivery, rapid iteration, and measurable business value.

Strong ownership mindset, including the ability to support solutions after deployment, troubleshoot issues, and continuously improve based on user feedback.

Preferred Candidate Profile

The ideal candidate is a hands-on engineer who can move between business discovery, technical design, AI-enabled prototyping, backend development, data integration, and cloud deployment. They should be comfortable taking loosely defined business needs and turning them into working solutions that improve operational visibility, reduce manual effort, improve decision-making, or strengthen exception management.

This person should not be limited to one application or one use case. They should be able to support a portfolio of AI-enabled initiatives, reuse patterns where appropriate, and help scale successful prototypes into maintainable business tools