Associate AI Pattern Engineer Job at FinXL (Sydney CBD)

Senior Software Engineer - Build AI Tools

This role sits within the newly formed GenAI Security team, which is responsible...

Location

United Kingdom , Belfast

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

Highly motivated self-starter with excellent interpersonal and problem-solving skills
Bachelor’s degree or equivalent work experience
Good oral and written communication skills
Significant relevant industry work experience
Experience of the full lifecycle of design, implementation and running of enterprise software solutions involving cross functional team collaboration
Expertise in a major programming language such as Python and/or Go, and associated tooling (Git, Maven, IDEs, Jenkins, Bitbucket etc)
Expertise in designing and implementing secure APIs and libraries
Experience in Generative AI, LLM frameworks, LLM prompt engineering and/or adversarial testing is a bonus
Experience with Cyber engineering and Operations, which could include DevSecOps or MLSecOps
Experience contributing to the architecture and design (architecture, design patterns, reliability, scaling) of new and current systems

Job Responsibility

Designing, developing, optimizing, and enhancing a GenAI prompt security platform to protect firm AI/LLM-based applications from adversarial attacks and prompt injections
Building and automating a security testing framework to validate protection mechanisms for various LLM use cases
Owning solutions that are expected to operate and perform at scale across the organisation
Collaboration with multiple stakeholders and partners across Engineering and Operations as well as partner teams within the wider Citi organisation, across different time zones

What we offer

27 days annual leave (plus bank holidays)
A discretional annual performance related bonus
Private Medical Care & Life Insurance
Employee Assistance Program
Pension Plan
Paid Parental Leave
Special discounts for employees, family, and friends
Access to an array of learning and development resources

Fulltime

AI Engineer - Insurance Domain

The AI Engineer role focuses on developing AI solutions for the insurance sector...

Location

United States , Warren

Salary:

87120.00 - 181500.00 USD / Year

NTT DATA

Expiration Date

Until further notice

Requirements

3+ years of professional experience in AI/ML engineering, with demonstrated delivery of production-grade AI systems
3+ years hands-on experience building and deploying LLM-powered applications using frameworks such as LangChain, LlamaIndex, or Semantic Kernel
3+ years proven experience implementing MLOps pipelines in cloud environments (Azure preferred)
3+ years experience developing AI agents or automation workflows using agentic frameworks
2+ years experience in financial services, insurance, or regulated industries is strongly preferred
Experience with P&C insurance workflows such as FNOL processing, claims triage, underwriting decisioning, or actuarial modeling
Familiarity with insurance regulatory requirements including NAIC guidelines and data privacy standards (CCPA, GDPR)
Experience implementing responsible AI principles — fairness, explainability, and bias mitigation — in regulated environments
Microsoft certifications: Azure AI Engineer Associate (AI-102) or Azure Data Scientist Associate (DP-100) preferred
Exposure to Data Mesh patterns and publishing AI model outputs as domain data products

Job Responsibility

Generative AI & LLM Engineering: Design, fine-tune, and deploy Large Language Models (LLMs) for insurance-specific use cases including document intelligence, claims summarization, policy interpretation, and underwriting Q&A
Build Retrieval-Augmented Generation (RAG) pipelines using vector databases (e.g., Azure AI Search, Pinecone, ChromaDB) to ground LLM outputs in enterprise knowledge bases
Develop prompt engineering frameworks and systematic evaluation pipelines to ensure LLM output quality, consistency, and safety in regulated insurance contexts
Integrate LLM capabilities with internal data platforms via LangChain, LlamaIndex, or Semantic Kernel
Evaluate and benchmark foundational models (OpenAI GPT-4o, Azure OpenAI, Claude, Mistral, Llama) against insurance-specific tasks to guide platform selection
AI Agents & Automation: Architect and implement autonomous AI agents capable of multi-step reasoning, tool use, and decision-making for workflows such as FNOL triage, claims routing, policy lookup, and compliance checks
Build agentic frameworks using patterns such as ReAct, Chain-of-Thought, and Tool-Augmented Agents to handle complex, multi-turn insurance workflows
Design human-in-the-loop (HITL) checkpoints and escalation logic to ensure AI agents operate within defined risk and compliance boundaries
Integrate agents with internal APIs, data platforms, and enterprise systems using orchestration tools such as Azure Logic Apps, Apache Airflow, or Databricks Workflows
Develop guardrails, monitoring, and audit logging for all deployed agents to meet regulatory and governance standards

Fulltime

Associate Data Engineer

You’ll design and build scalable, AI‑ready solutions across data, cloud, and bus...

Location

United Kingdom , Manchester

Salary:

Not provided

ANS Group

Expiration Date

Until further notice

Requirements

A curious problem‑solver with strong analytical thinking and an interest in AI, cloud, and data‑driven decision‑making
Comfortable learning in ambiguous environments, experimenting with new tools, and building solutions through hands‑on experience
A collaborative communicator with some exposure to cloud, scripting, or automation through study, projects, or self‑learning
A degree in a relevant field is preferable (e.g. Computer Science, Data, Engineering, Cloud, Business Technology, or similar)
A solid foundation in digital systems, with some exposure to cloud platforms, coding, or data tools through study, projects, or self‑learning
An interest in AI, modern delivery practices (Agile/DevOps), and how scalable technology solutions are built in the real world

Job Responsibility

Platform Engineering: Deploy secure, repeatable AI cloud environments using Infrastructure as Code
Support CI/CD pipelines for AI infrastructure and data deployments
Help manage core platform services including security, networking, and monitoring
Collaborate with AI & Data Engineers and document reusable platform patterns
Data Engineering: Build and maintain data pipelines for AI and automation use cases
Prepare structured datasets, vector stores, and model‑ready data
Implement monitoring and validation to ensure data quality and reliability
Create reusable data components aligned to platform and business needs
Business Technology: Translate business problems into clear AI and automation requirements
Support discovery sessions, workshops, and solution design

What we offer

Hybrid/ Remote Working
Private Medical Care
Pension Scheme
25 days’ holiday, plus buy up to 5 more days
Birthday off
Celebration day
5 days’ additional holiday in the year you get married
5 volunteer days
Private health insurance
Pension contribution match and 4 x life assurance

Fulltime

New

Senior Lead Technology Risk Officer - Application Domain, SDLC, DevOps and AI

The Application Risk Domain Officer operates within Technology Risk Management (...

Location

United States , Charlotte

Salary:

159000.00 - 254000.00 USD / Year

Wells Fargo

Expiration Date

June 03, 2026

Requirements

7+ years of Technology Risk experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
7+ years of experience spanning software engineering, DevSecOps, platform engineering, cloud engineering, application security, with direct experience in technology risk, technology controls, or second-line risk oversight in complex technological environments
deep hands-on knowledge of modern SDLC and DevOps practices, including source control, code review, branching and release strategies, CI/CD design, automated testing, deployment automation, and production change controls
experience performing technical risk assessments, control evaluations, and credible challenge across SDLC, DevOps, software supply chain, cloud, and AI-enabled engineering environments to translate findings into concise risk narratives, control gaps, remediation expectations, and executive reporting
ability to read and interpret architecture patterns, deployment designs, control implementations, technical standards, and engineering evidence with sufficient depth to challenge first-line technical decisions
experience with AI governance and controls, or model risk concepts as applied to engineering productivity tools, agentic workflows, or AI-assisted software delivery, and the risks associated with them
strong judgment, analytical rigor, and communication skills with the ability to influence senior stakeholders while maintaining credibility with technical teams
knowledge of industry frameworks and guidance relevant to technology and security risk, such as NIST, SSDF, COBIT, FFIEC guidance, ISO 27001, or similar frameworks
strong technical understanding of developer platforms and engineering toolchains, including technologies such as GitHub or GitLab, Jenkins or Azure DevOps, artifact repositories, package managers, Terraform, containers, Kubernetes, and major cloud platforms
hands-on familiarity with engineering and security tooling used in modern delivery environments, including static and dynamic analysis, software composition analysis, container security, CSPM, CI/CD security controls, and observability platforms

Job Responsibility

Provide expert second-line oversight of modern engineering practices, including application architecture patterns, secure SDLC, CI/CD, DevSecOps, platform engineering, infrastructure as code, containerized workloads, and production release controls
Own second-line technology risk coverage and provide thought leadership across the application risk domain, partnering closely with first-line engineering, controls and technology teams to drive consistent oversight of application architecture, development practices, deployment pipelines, and supporting engineering controls
Perform technically rigorous assessments of source control workflows, branching strategies, build systems, test automation, artifact repositories, package dependencies, deployment orchestration, and runtime platform configurations to identify control weaknesses and systemic risk
Evaluate the integrity of software delivery pipelines end to end, including code provenance, pipeline trust boundaries, secrets handling, approval models, environment segregation, artifact immutability, and rollback or recovery capabilities
Lead deep-dive technical risk reviews of complex delivery environments and modernization programs, converting architecture, pipeline, and operational observations into clear risk statements, root causes, and targeted remediation expectations
Analyze developer ecosystems and engineering tool chains at a practitioner level, including repositories, CI runners, build agents, package managers, IaC frameworks, containers, Kubernetes, cloud services, and observability stacks
Evaluate AI-enabled engineering capabilities, including code assistants, prompt-based development workflows, automated test generation, agentic tooling, and model-integrated developer platforms, with emphasis on data exposure, unsafe code generation, traceability, and human review requirements
Review design and implementation patterns for application and platform controls, such as policy-as-code, secrets management, service identity, environment hardening, logging, monitoring, drift detection, and release gating
Develop technically meaningful risk indicators and challenge metrics for SDLC, DevOps, and AI-enabled engineering, such as deployment control exceptions, pipeline bypasses, privileged access patterns, dependency exposure, control coverage gaps, and remediation aging
Serve as a trusted technical risk partner to engineering, security, architecture, and control teams by applying expert discipline knowledge to high-impact decisions and shaping resilient engineering practices across the enterprise

Fulltime

Senior Solution Engineer (Innovation Hub - AI Workforce)

Microsoft Innovation Hub empowers customers to overcome their business challenge...

Location

Singapore , Singapore

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

8+ years of technical pre-sales or technical consulting experience OR Bachelor's Degree in Computer Science, Information Technology, or related field AND 8+ years of experience OR equivalent experience
Enterprise Architect Experience: Proven experience as an Enterprise Architect, designing and implementing large-scale, complex solutions that align with business goals and technical requirements
Consultative Selling: Proven experience in a consultancy role, providing expert guidance and strategic recommendations to customers
Strategic & Structured Facilitator: Validated customer experience in requirements capture
prioritization
capturing evidence and impact to quantify business value
issue, risk and constraint identification with a focus on strategic goals and outcomes
AI Solution Design Experience: Expertise in designing architectures, building, and deploying AI solutions with Microsoft 365, primarly Microsoft Copilot
Experience with cloud and hybrid infrastructures, adjacent technologies, architecture designs, migrations, and industry standards
Understanding of AI related Azure services

Job Responsibility

Delivering customer engagements: Prepare and deliver technical engagements including strategy sessions, envisioning workshops, architecture design sessions and rapid prototyping to demonstrate key capabilities, validate against identified risks and finalize technology choices
AI Transformation Leadership: Be the trusted voice within the business and for customers on the latest AI platform and technology trends, guiding their transformation journeys
Strategic Vision and Planning: Own and execute a clear strategic vision for AI transformation initiatives on a set of targeted accounts, aligning with organizational goals and customer needs by collaborating and orchestrating cross-functional teams
Solution Design and Architecture: Develop comprehensive solution architectures based on patterns and practices that are tied to customer requirements and ensure that solutions are scalable, secure and optimized for performance
Cross Platform Collaboration: Adopt a holistic approach to integrate capabilities across the entire cloud platform, identifying synergies and optimizing cross-platform integration
Technical Depth: Maintain and grow expertise in creating business value on top of the business applications including sales, services and marketing and Microsoft 365 platform, including deep knowledge of Microsoft Copilot to support AI transformation initiatives
Technical Sales and Sales Leadership: Act as a strategic change agent within the business to shape Microsoft's programs and engineering offerings

Fulltime

New

Senior AI Engineer

Shutterfly is seeking a Senior AI Engineer (Contractor) to accelerate the design...

Location

United States , Eden Prairie

Salary:

Not provided

Abotts

Expiration Date

Until further notice

Requirements

8+ years of professional software / ML engineering experience, with 2+ years building production generative AI or agentic systems
Expert-level proficiency in Microsoft Copilot Studio — agent design, topics, custom connectors, Power Platform integration, governance, and lifecycle management
Hands-on expertise with Azure AI Foundry (formerly Azure AI Studio) — model deployment, prompt flow, agent service, evaluations, and content safety
Production experience with Anthropic Claude — Anthropic SDK, prompt caching, tool use, MCP (Model Context Protocol), and multi-turn agent design
Strong working knowledge of Google Cloud Platform — Vertex AI, Gemini, Agent Builder, BigQuery, Cloud Run, and IAM
Proficiency in Python and at least one of TypeScript/Node.js or C#/.NET
Solid grounding in RAG architectures, vector databases (Azure AI Search, Pinecone, Vertex Vector Search), embeddings, and semantic retrieval
Experience with LLM evaluation frameworks, observability (LangSmith, Azure AI Foundry evaluations, custom telemetry), and A/B testing of AI systems
Experience integrating AI with Microsoft 365 (Graph API, Teams, SharePoint, Outlook) and enterprise identity (Entra ID / OAuth2)
Strong understanding of responsible AI, data privacy (GDPR, CCPA), and enterprise security practices

Job Responsibility

Design, build, and deploy enterprise-grade AI agents, copilots, and automation workflows that integrate with Microsoft 365, internal systems, and customer-facing applications
Microsoft Copilot Studio: Develop and operationalize agents and low-code/pro-code solutions — custom topics, plugins, knowledge sources, and connectors
Azure AI Foundry: Architect and implement model orchestration, retrieval-augmented generation (RAG), evaluation, and guardrails using model catalog, prompt flow, agent service, and content safety
Anthropic Claude: Integrate Claude models (Opus, Sonnet, Haiku) via the Anthropic API and Bedrock — including prompt caching, tool use, extended thinking, and agentic patterns
Google Cloud Platform: Build and operate AI services using Vertex AI, Gemini, Agent Builder, BigQuery, and associated MLOps tooling
Lead end-to-end model lifecycle: data preparation, fine-tuning/adaptation, evaluation, deployment, observability, and continuous improvement
Establish and enforce responsible AI practices — security, privacy, content safety, bias mitigation, prompt injection defense, and auditability — in alignment with Shutterfly enterprise standards
Partner with Systems Engineering, Security, and Data teams to integrate AI workloads with identity (Entra ID), data platforms, and CI/CD pipelines
Mentor internal engineers and developers
produce reusable patterns, reference architectures, and documentation that elevate the team's AI maturity

Principal Consultant A2 - Infra

Microsoft Industry Solution - Global Center Innovation and Delivery Center (GCID...

Location

India , Hyderabad

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor’s degree in computer science, Engineering, or related field AND 3+ years leadership experience in relevant area of business. Higher Education Preferred
OR master’s degree in computer science, Information Technology, Engineering, or related field AND 6+ years’ experience in technology solutions, practice development, architecture, consulting, and/or Cloud Infrastructure domain
Highly proficient & solid Customer facing Project experience involving solution design, project envisioning, planning, development, and deployment of complex solutions with minimum of 10 plus years
Must have a proven record of delivering technical solutions
2+ years managing multiple projects or portfolios
1+ year(s) experience leading blended, multidisciplinary teams
Preferred Qualifications: Overall minimum 20+ Year of industry experience
Technical or Professional Certification in Cloud Infrastructure domain
Open to travel domestically and internationally and work with different cultures and customers
Technical certifications based on domain/service line (e.g., Azure, Security, Dynamics)

Job Responsibility

AI-First Delivery Leadership: Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable
Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes
Drive engineering excellence through reusable components, accelerators, and scalable architecture
Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements
Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches
Act as a technical point of contact for clients, translating business requirements into scalable technical solutions
Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes
Ability to step into at risk projects, quickly assess issues, and establish a credible path to recovery or exit
Engineering Excellence: Champion high-quality engineering practices across all delivery engagements
Ensure adherence to coding standards, architectural integrity, and performance benchmarks

Fulltime

AI Engineer

As an AI Engineer, you’ll play a key role in designing, building and operating A...

Location

India , Mumbai

Salary:

Not provided

Collinson

Expiration Date

Until further notice

Requirements

A strong foundation in software engineering, with hands-on experience building, shipping and operating scalable, production-grade systems
Proven experience working with modern JavaScript and TypeScript stacks, including Node.js and associated backend frameworks, and confidence contributing to clean, maintainable codebases
Practical experience integrating large language models into real applications, using APIs such as OpenAI, Anthropic or similar, with an understanding of prompt design, evaluation and operational trade-offs
Confidence designing and working with APIs and backend services, including RESTful architectures and integration patterns that support reliability and scale
Familiarity with cloud-native environments and production tooling, including containerisation, monitoring and deployment practices, ideally within AWS-based ecosystems
Experience working with data stores such as PostgreSQL, MongoDB and or vector databases, with an understanding of how data design supports AI driven use cases
The ability to reason about cost, latency, privacy and risk when designing AI powered systems, and to make pragmatic engineering decisions within real-world constraints
Strong problem solving skills and attention to detail, with a mindset oriented toward iteration, evidence and continuous improvement
The ability to communicate complex technical concepts clearly and simply to a range of audiences, from engineers to product partners and non-technical stakeholders
Curiosity and adaptability, with a genuine interest in staying current with emerging AI tools, techniques and best practices, and applying them thoughtfully rather than reactively

Job Responsibility

AI Feature Design & Delivery – Design, build and run AI powered features using large language models, translating product ideas into reliable, scalable production systems that deliver measurable impact
LLM Integration & System Architecture – Integrate LLMs into existing applications and services, shaping backend architectures and APIs that balance performance, cost, security and maintainability
Prompt Engineering & Model Optimisation – Develop, test and refine prompt strategies to improve model accuracy, safety, latency and cost efficiency across different use cases
Hands-On Engineering – Build and maintain backend services and APIs using TypeScript and modern frameworks, contributing clean, well documented and maintainable code aligned with engineering best practice
Cross-Functional Collaboration – Work closely with product, data and design partners to identify high value AI opportunities and shape solutions that are feasible, testable and aligned to user needs
Evaluation & Monitoring – Define and implement evaluation approaches for LLM based systems, including logging, metrics and experimentation, to continuously improve quality and reliability in production
Scalable AI Patterns – Contribute to shared approaches, architectural patterns and standards for building AI driven features across the platform
Risk, Privacy & Cost Awareness – Make informed engineering decisions that consider data privacy, model risk, operational resilience and commercial constraints
Continuous Learning & Innovation – Stay current with emerging AI technologies, tools and techniques, proactively recommending improvements that enhance outcomes for users and teams

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Associate AI Pattern Engineer

Job Description

Job Responsibility

Requirements

What we offer

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