Project Brains

AI Engineer (GenAI &amp; Agentic AI) – Financial Services Workflows
International Tech Co
Birmingham, UK (Onsite)
Full-time
Role Overview
International Tech Co is hiring hands-on AI Engineers to build enterprise-grade GenAI and Agentic AI solutions for complex financial-services workflows. You will focus on AI-assisted exception classification, triage, root-cause analysis, impact assessment, workflow orchestration, and remediation across large-scale transaction and data-processing environments. This role requires strong Python, SQL, API, and software-engineering fundamentals, plus practical experience building LLM and agentic AI applications with controls, reliability, and auditability in mind.
What You’ll Do (Key Responsibilities)
<ul>
<li>Build AI workflows for exception classification, triage, root-cause analysis, impact assessment, and remediation recommendations.
</li>
<li>Develop agentic workflows including orchestration, tool​/​function calling, state management, and human-in-the-loop validation.
</li>
<li>Correlate new exceptions with historical issues, known root causes, business rules, and transaction​/​data attributes.
</li>
<li>Build Python and SQL-based services to query, transform, and analyze structured enterprise datasets.
</li>
<li>Integrate AI applications with enterprise APIs, databases, workflow​/​ticketing platforms, and internal data sources.
</li>
<li>Develop reusable tools and services that AI agents can invoke for retrieval, investigation, analysis, and workflow execution.
</li>
<li>Apply RAG​/​context retrieval to search regulatory documents, historical knowledge, and issue repositories where needed.
</li>
<li>Implement confidence scoring, validation, guardrails, traceability, and audit-ready evidence for AI-generated outcomes.
</li>
<li>Build backend services and APIs using Python and FastAPI.
</li>
<li>Implement testing, logging, evaluation, observability, exception handling, and production engineering best practices.
</li>
<li>Collaborate with AI engineers, architects, business analysts, data engineers, and application teams.
</li>
</ul>
Minimum Qualifications (Must-Have)
<ul>
<li>Strong​/​expert Python skills with solid software-engineering fundamentals (Git, code quality, testing, production readiness).
</li>
<li>Strong SQL and data analysis skills, including complex relational queries and working with structured enterprise datasets.
</li>
<li>Strong hands-on experience building GenAI​/​LLM applications for real workflows (not only demos).
</li>
<li>Hands-on experience implementing agentic AI workflows with orchestration, tool​/​function calling, and state management.
</li>
<li>Strong experience building and integrating APIs, including Python​/​FastAPI services and REST​/​JSON integrations.
</li>
<li>Proven ability to solve ambiguous problems and perform root-cause analysis across data, systems, and process context.
</li>
</ul>
Agentic AI Experience (Required)
<ul>
<li>Hands-on experience with at least one agent​/​workflow orchestration framework such as LangGraph, Google ADK, CrewAI, AutoGen, Semantic Kernel, or an equivalent custom framework.
</li>
<li>Ability to implement patterns such as Input → Classification → Tool​/​Data Retrieval → Investigation → Reasoning → Validation → Action.
</li>
</ul>
Data &amp; Integration Experience (Required)
<ul>
<li>Experience working with structured transaction, event, or operational data in enterprise environments.
</li>
<li>Experience integrating across multiple data sources and systems, including workflow​/​ticketing data and historical issue​/​event repositories.
</li>
<li>Comfort handling incomplete, inconsistent, or changing enterprise data and building resilient correlation logic.
</li>
</ul>
GenAI Controls, Safety, and Quality (Required)
<ul>
<li>Experience implementing confidence-based or known-vs-unknown classification approaches.
</li>
<li>Working knowledge of RAG​/​semantic matching and contextual retrieval.
</li>
<li>Working knowledge of LLM​/​agent evaluation, output validation, and guardrails.
</li>
<li>Ability to design deterministic + LLM hybrid workflows with traceability and audit trails.
</li>
<li>Familiarity with observability practices for AI systems (logging, metrics, evaluation runs, error analysis).
</li>
</ul>
Preferred Qualifications (Nice-to-Have)
<ul>
<li>Financial-services domain exposure (preferred but not mandatory), including regulatory reporting, capital markets, trade lifecycle, post-trade processing, transaction reporting, reconciliations, exception management, risk, or controls.
</li>
<li>Familiarity with regulations such as EMIR, MiFID II, or SFTR.
</li>
<li>Exposure to cloud environments (AWS, GCP, or Azure).
</li>
</ul>
What Success Looks Like
<ul>
<li>You rapidly build working prototypes that connect to real enterprise data and systems and then harden them into reliable services.
</li>
<li>You produce agentic workflows that are controllable, testable, observable, and safe for enterprise use with human-in-the-loop gates.
</li>
<li>You deliver measurable improvements in exception classification accuracy, investigation speed, and remediation consistency with clear auditability.
</li>
</ul>
International Tech Co is an equal opportunity employer.
Please get in touch on <a href="mailto:info@projectbrains.io" rel="nofollow noopener" target="_blank">info@projectbrains.io</a>

Client Deployed Specialist (Banking FS)

Client Deployed Specialist (Banking FS)

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