Corporate KYC Principle Software Engineer

Hackajob Ltd; Glasgow; On-site; GBP 90,000 - 110,000; Full time

Job summary

Hackajob Ltd partners with JPMorganChase to hire for a senior AI/data engineering leadership role focused on enterprise-scale agentic AI systems, data platforms, and secure governance.

You will architect scalable data and AI platforms, drive adoption of cutting-edge practices, and influence senior technical leaders across finance and technology teams.

Qualifications

• Hands-on enterprise-scale system design and delivery experience.
• Hands-on AI/ML system design with LLMs and agentic architectures.
• Expert Python and/or Java programming skills.
• Deep knowledge of cloud, data engineering and observability tools.

Responsibilities

• Architect and implement scalable engineering frameworks and solutions.
• Develop secure production code for data-intensive platforms and mentor engineers.
• Create reusable software frameworks used across teams.
• Design and govern agentic AI systems with governance controls.
• Set engineering standards for LLM applications, RAG pipelines, vector stores and model serving.
• Drive adoption of advanced technical methods and work with leadership on strategy.
• Serve as SME in data engineering, platform architecture, or AI systems.
• Advise cross-functional teams on technical matters within domain.
• Influence senior stakeholders on strategy and direction.
• Govern agentic AI workflows with guardrails for validation and reuse.

Skills

System design

Application development

Testing

Operational stability

AI/ML design

LLM architectures

Python

Java

Regulated environments

Tools

Spark

PySpark

Kafka

Redis

Dynatrace

Splunk

Grafana

Airflow

Temporal

Databricks

Snowflake

AWS

Azure

GCP

Job description

Salary: £100,000 - 100,000 per year

Requirements

• We require hands-on practical experience delivering system design, application development, testing, and operational stability at enterprise scale.
• We require hands-on experience designing and deploying production AI/ML systems, including LLM-based applications and agentic architectures with tool use, memory, and multi-step reasoning in regulated environments.
• We require expert-level experience in one or more programming languages, particularly Python and/or Java.
• We require advanced knowledge of software application development and technical processes, with considerable depth in one or more disciplines such as cloud, AI/ML, or data engineering.
• We require experience in large-scale data processing, microservices, API design, Kafka, Redis, MemCached, observability tools such as Dynatrace, Splunk, and Grafana, and orchestration frameworks such as Airflow and Temporal.
• We require advanced working knowledge of relational and NoSQL databases, vector stores, data lake architectures, and data governance.
• We require practical cloud-native experience with AWS, Azure, or GCP.
• We require the ability to present and effectively communicate with senior leaders and executives.
• We require demonstrable experience designing and leading adoption of agentic AI-enabled development practices across teams, including setting standards for human-in-the-loop validation, auditability and traceability of changes, and secure handling of sensitive data.
• We require a strong understanding of responsible AI use and control expectations in engineering workflows, including security and resiliency implications, data sensitivity, and risk-based governance, with the ability to influence senior technical leaders on safe scaling patterns and reuse.
• Preferred experience includes modern data platforms such as Databricks or Snowflake.
• Preferred experience includes deep hands-on work with Spark/PySpark and other big data processing technologies.
• Preferred expertise includes open-source table formats and catalog services such as Apache Iceberg.
• Preferred experience includes LLM orchestration frameworks and model serving infrastructure or managed endpoints such as AWS Bedrock or Azure OpenAI.
• Preferred familiarity includes AI evaluation and observability practices, such as evals frameworks, red-teaming, prompt drift detection, and cost and latency monitoring for LLM workloads.
• Preferred understanding includes agentic design patterns and how to constrain agent autonomy in high-stakes financial workflows.
• Preferred awareness includes AI risk and regulatory considerations relevant to AI use in financial decision-making.

Responsibilities

• We architect and implement complex, scalable engineering frameworks and solutions using modern software design principles.
• We develop secure, high-quality production code for data-intensive applications and platforms, and review and mentor other engineers.
• We create durable, reusable software frameworks and patterns that are leveraged across teams and functions.
• We design and govern agentic AI systems, including multi-agent workflows, tool-use integrations, and human-in-the-loop controls appropriate for regulated financial services environments.
• We establish engineering standards for LLM-based applications, including RAG pipelines, embedding workflows, vector store integrations, and model serving, ensuring safety, observability, and reproducibility at scale.
• We drive adoption of advanced technical methods and practices aligned with the latest industry standards and product development methodologies.
• We serve as the functions go-to subject matter expert in one or more areas of focus within data engineering, platform architecture, or AI systems.
• We advise cross-functional teams on technological matters within our domain of expertise.
• We influence leaders and senior stakeholders across business, product, and technology teams on technical strategy and direction.
• We architect and govern agentic AI-enabled engineering workflows using enterprise-authorized tools within the work environment to improve delivery speed, code quality, and operational outcomes at scale, while defining guardrails for validation, security, resiliency, and reuse across teams.
• We apply knowledge of tools within the software development life cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation at scale.

Technologies

• Agentic AI
• AI
• Airflow
• API
• AWS
• Architect
• Azure
• Big Data
• Cloud
• Databricks
• Dynatrace
• GCP
• Grafana
• Support
• Java
• Kafka
• LLM
• Marketing
• Model Serving
• NoSQL
• Python
• PySpark
• RAG
• Redis
• Security
• Snowflake
• Spark
• Splunk
• microservices

More

hackajob is partnering directly with JPMorganChase to hire for this role. We are a global leader in financial services, providing strategic advice and products to the worlds most prominent corporations, governments, wealthy individuals, and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do, and we strive to build trusted, long-term partnerships to help our clients achieve their business objectives. This role sits within our Corporate Sector and Corporate Functions team, where our professionals support areas ranging from finance and risk to human resources and marketing. We offer an agile data engineering environment focused on building a trusted, market-leading Global Know Your Customer and Risk Assessment Data Platform in a secure, stable, and scalable way. We value diversity and inclusion, and we provide reasonable accommodations for applicants and employees with religious practices and beliefs, mental health needs, or physical disability needs.

last updated 38 week of 2026