Client Deployed Specialist (Onsite) - #2167555

AI Engineer (GenAI & 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)

- Build AI workflows for exception classification, triage, root-cause analysis, impact assessment, and remediation recommendations.

- Develop agentic workflows including orchestration, tool/function calling, state management, and human-in-the-loop validation.

- Correlate new exceptions with historical issues, known root causes, business rules, and transaction/data attributes.

- Build Python and SQL-based services to query, transform, and analyze structured enterprise datasets.

- Integrate AI applications with enterprise APIs, databases, workflow/ticketing platforms, and internal data sources.

- Develop reusable tools and services that AI agents can invoke for retrieval, investigation, analysis, and workflow execution.

- Apply RAG/context retrieval to search regulatory documents, historical knowledge, and issue repositories where needed.

- Implement confidence scoring, validation, guardrails, traceability, and audit-ready evidence for AI-generated outcomes.

- Build backend services and APIs using Python and FastAPI.

- Implement testing, logging, evaluation, observability, exception handling, and production engineering best practices.

- Collaborate with AI engineers, architects, business analysts, data engineers, and application teams.

Minimum Qualifications (Must-Have)

- Strong/expert Python skills with solid software-engineering fundamentals (Git, code quality, testing, production readiness).

- Strong SQL and data analysis skills, including complex relational queries and working with structured enterprise datasets.

- Strong hands-on experience building GenAI/LLM applications for real workflows (not only demos).

- Hands-on experience implementing agentic AI workflows with orchestration, tool/function calling, and state management.

- Strong experience building and integrating APIs, including Python/FastAPI services and REST/JSON integrations.

- Proven ability to solve ambiguous problems and perform root-cause analysis across data, systems, and process context.

Agentic AI Experience (Required)

- 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.

- Ability to implement patterns such as Input → Classification → Tool/Data Retrieval → Investigation → Reasoning → Validation → Action.

Data & Integration Experience (Required)

- Experience working with structured transaction, event, or operational data in enterprise environments.

- Experience integrating across multiple data sources and systems, including workflow/ticketing data and historical issue/event repositories.

- Comfort handling incomplete, inconsistent, or changing enterprise data and building resilient correlation logic.

GenAI Controls, Safety, and Quality (Required)

- Experience implementing confidence-based or known-vs-unknown classification approaches.

- Working knowledge of RAG/semantic matching and contextual retrieval.

- Working knowledge of LLM/agent evaluation, output validation, and guardrails.

- Ability to design deterministic + LLM hybrid workflows with traceability and audit trails.

- Familiarity with observability practices for AI systems (logging, metrics, evaluation runs, error analysis).

Preferred Qualifications (Nice-to-Have)

- 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.

- Familiarity with regulations such as EMIR, MiFID II, or SFTR.

- Exposure to cloud environments (AWS, GCP, or Azure).

What Success Looks Like

- You rapidly build working prototypes that connect to real enterprise data and systems and then harden them into reliable services.

- You produce agentic workflows that are controllable, testable, observable, and safe for enterprise use with human-in-the-loop gates.

- You deliver measurable improvements in exception classification accuracy, investigation speed, and remediation consistency with clear auditability.

International Tech Co is an equal opportunity employer.

Please get in touch on [email protected]