Senior Machine Identity Security Engineer - AI governance Job at Dutech Systems (Charlotte)

Senior AI Engineer

Security is one of Microsoft’s highest priorities as customers face increasing d...

Location

United States , Multiple Locations

Salary:

119800.00 - 234700.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements
Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience
2–3+ years working with ML/AI systems (LLMs/GenAI, RAG, model serving, experimentation, or data pipelines)
Hands‑on engineering experience building distributed cloud services in Azure
Familiarity with security domains such as detection/response, SIEM/SOAR, identity, endpoint, or cloud security
Experience working with GenAI/LLM techniques: MCP, prompt engineering, retrieval/vector stores, agent/tooling frameworks, content safety, and evaluation platforms
Strong coding skills and comfort engaging deeply in design and implementation details

Job Responsibility

Build and prototype AInative features and system components, with a focus on iterative learning and shipping working code
Implement wellarchitected services, APIs, evaluation harnesses, and data pipelines that support AIbased security scenarios
Contribute to modeldriven features, including LLMbased reasoning, retrieval/RAG, grounding, routing, and safety guardrails
Design and evaluate ML/AI systems using metrics such as groundedness, precision/recall, latency, and cost
Apply responsible AI, security, and privacy requirements throughout the development lifecycle
Work with partners to integrate prototypes into production environments as part of broader engineering efforts
Work with crossdisciplinary teams (research, PM, engineering) to clarify requirements and land technical decisions
Participate in design reviews, code reviews, and handson technical discussions
Contribute to a culture of curiosity, scientific rigor, and customerobsessed problem solving

Fulltime

Senior AI / ML Engineer

We are seeking an experienced Senior ML to join our team and engage in a diverse...

Location

United Kingdom , London

Salary:

Not provided

BMT

Expiration Date

Until further notice

Requirements

Be a UK sole national
Have held no other nationality at any time
Have continuously resided in the United Kingdom for the past five years
Be able to obtain and maintain full UK security clearance in accordance with government vetting standards
Provide satisfactory evidence of identity, nationality, and residency as part of the clearance process
Ability to select, train, and tune models (classical ML and deep learning) using frameworks such as PyTorch, TensorFlow, or scikit-learn
perform robust validation and error analysis
Experience containerising and deploying models (e.g., Docker), implement CI/CD, monitoring, drift detection, and automated retraining on Azure/AWS/GCP as appropriate
Strong engineering skills in Python (typing, testing, packaging)
experience with version control (Git) and code review workflows

Job Responsibility

Designing, building, testing, and deploying machine-learning systems, applying robust software engineering practices and an in-depth understanding of model behaviour, performance, and limitations
Selecting and preparing data pipelines for model training and inference
Implementing, training, evaluating, and optimising machine-learning models, continually improving them through iterative experimentation and additional data
Creating scalable and automated ML pipelines, including feature extraction, model training, validation, packaging, deployment, and monitoring
Applying standardised engineering and evaluation methods, producing clear technical documentation and communicating design choices, performance outcomes, and limitations
Evaluating data integrity and suitability for ML workflows, and advising on transformations, feature representation, and schemas needed for efficient training and inference
Applying engineering-focused data modelling and system design techniques to create, modify, or maintain ML-relevant data structures, feature stores, and associated components
Supporting alignment of data structures, model interfaces, and infrastructure components to ensure efficient and scalable ML system operation

What we offer

Private Medical (family coverage)
Enhanced Pension
18 weeks enhanced maternity pay (after a qualifying period of 1 year)
Family friendly policies
Committed to an inclusive culture
Wellbeing Fund – an annual fund for personal hobbies or interests
26 Days Annual Leave (plus bank holidays)
Holiday Trading
Retail Vouchers
Professional Subscriptions

Fulltime

Senior Enterprise Agentic AI Engineer

Planet DDS is building a centralized intelligence layer focused on transforming ...

Location

United States , Irvine

Salary:

177000.00 - 221000.00 USD / Year

Planet DDS

Expiration Date

Until further notice

Requirements

5-7 years of experience in software engineering or applied machine learning
2+ years building production deployments of agentic AI systems (tool‑using LLMs or multi‑agent workflows) with measurable business outcomes
Demonstrated experience productionizing AI or LLM-based systems
Proficiency in Python/TypeScript and building API‑first services with CI/CD
Hands-on experience with prompt engineering, evaluation, and optimization
Working knowledge of enterprise lakehouse architectures, including Delta Lake, medallion patterns, streaming ingestion, governance (Unity Catalog), and designing data layers that support high‑performance AI/agentic workflows
Proven ability to integrate Azure OpenAI or similar LLM platforms into orchestrated workflows
Experience designing and orchestrating multi-step, event-driven workflows using modern cloud-native services for serverless execution, workflow orchestration, messaging, and event-driven architecture
Experience designing and deploying cloud-native AI workflows in Microsoft Azure
Demonstrated ability to implement guardrails, output validation, and human‑in‑the‑loop patterns in production

Job Responsibility

Design, build, and scale production-grade agentic workflows that observe operational signals, reason across data, and take or recommend actions such as alerts, task creation, and decision support
Implement multi‑agent patterns (planner/worker, toolformer, delegate/reviewer) with deterministic and human‑in‑the‑loop controls
Architect an agentic intelligence layer atop the enterprise data lakehouse
Own the AI execution layer, including prompt architecture, orchestration, evaluation, monitoring, logging, and tool creation including but not limited to MCP
Translate business needs and operational challenges into clear technical approaches and delivery plans, resulting in scalable, reusable AI solutions
Partner closely with data engineering to define AI-ready schemas and data contracts
Instrument workflows with tracing, cost/perf dashboards, evaluation harnesses (automated + human), and drift monitoring
Ensure AI systems are secure, governed, auditable, and reliable
Drive solutions from concept to production without heavy process or handoffs

What we offer

Medical, dental and vision insurance
Health Savings Account
Flexible Spending Accounts
Telehealth
401(k) and 401(k) match
Life and AD&D insurance
Short-Term and Long-Term Disability
FTO or Vacation
Sick Time
Employee Well-Being program

Fulltime

Global Senior Security Manager

We are seeking a seasoned security leader to partner with our CISO in protecting...

Location

United States , New York

Salary:

150000.00 - 210000.00 USD / Year

Alter Domus

Expiration Date

Until further notice

Requirements

10+ years in cybersecurity with at least 5 years in a leadership role managing global, cross-functional teams
Proven track record of representing security at C-suite and board level, translating complex risk into clear business narrative
Experience in financial services or a similarly regulated industry (FCA, PRA, DORA, SOX, PCI-DSS)
Familiarity with deploying AI security frameworks such as NIST AI RMF 1.0, MITRE ATLAS, and financial services AI governance standards
Practical knowledge of implementing AI-powered security tools to automate detection, response, and guardrail enforcement
Familiarity with AI model risk, LLM threat surfaces, data poisoning, prompt injection, and adversarial ML attack vectors
Familiarity with enterprise security tools
Broad exposure to endpoint protection, vulnerability management, CSPM, DLP, and email security platforms
CISSP, CISM, or CRISC — one or more preferred
CCSP or equivalent cloud security credential

Job Responsibility

Support CISO in key decision making and regulatory meetings — presenting risk posture, programme status, and strategic recommendations with clarity and confidence
Build, mentor, and manage high-performing, globally distributed security teams spanning multiple time zones and functions
Define and execute the enterprise security roadmap aligned with business strategy and applicable regulatory requirements (FCA, PRA, DORA, SOX, PCI-DSS)
Lead end-to-end transformation of Identity & Access Management (IAM) and Privileged Access Management (PAM), including strategy, tooling selection, and programme delivery
Drive implementation of an Identity Governance & Administration (IGA) framework — encompassing joiner/mover/leaver processes, role engineering, access certification, and policy enforcement
Oversee deployment and maturation of PAM controls, credential vaulting, just-in-time access, and session monitoring to eliminate over-privileged accounts across the enterprise
Establish access management metrics and KPIs reported to executive leadership and regulators
Lead the Zero Trust Architecture (ZTA) transformation programme — defining principles, technology roadmap, and phased rollout across on-premises, cloud, and hybrid environments
Drive AI-augmented network and security architecture, leveraging machine learning for anomaly detection, automated policy enforcement, and predictive threat modelling
Build and operationalise a Network Operations (NetOps) operating model — defining governance, runbooks, escalation paths, and SLA frameworks for a globally resilient network

What we offer

Support for professional accreditations
Flexible arrangements, generous holidays, plus an additional day off for your birthday
Continuous mentoring along your career progression
Active sports, events and social committees across our offices
24/7 support available from our Employee Assistance Program
The opportunity to invest in our growth and success through our Employee Share Plan
Plus additional local benefits depending on your location

Fulltime

Senior Security Analyst

You will work as part of a 24/7 Global Security Operations Centre. The Senior SO...

Location

United Kingdom

Salary:

Not provided

Admiral Group Plc

Expiration Date

Until further notice

Requirements

3+ years’ experience as a Senior SOC Analyst within an internal SOC environment
Strong experience in a SOC environment, including handling high‑severity incidents
Deep understanding of attacker tradecraft across endpoint, identity, cloud, and email attack surfaces
Hands‑on experience with SIEM, EDR, and security investigation platforms
Proven threat hunting experience using dashboards, structured queries, and behavioural analytics
Experience tuning detections and implementing well‑governed exclusions without increasing risk
Ability to clearly document investigations, decisions, and outcomes
Experience using AI or machine‑learning features within security products
Familiarity with SOAR workflows and automation concepts
Knowledge of detection engineering concepts and use‑case lifecycle management

Job Responsibility

Act as senior escalation point for complex/high-severity alerts across SIEM, EDR, cloud and identity platforms
Lead end-to-end incident response (investigation, containment, eradication, and post-incident review)
Correlate alerts with threat intelligence and business context to assess risk and impact
Produce clear investigation summaries for technical and non-technical stakeholders
Collaborate closely with Incident Response during escalations
Use AI-enabled features across SOC tooling to accelerate analysis and investigations
Apply strong judgement to validate AI outputs and avoid automation bias
Provide feedback to improve tooling, workflows, and AI effectiveness
Support development of safe and consistent AI usage standards within the SOC
Conduct proactive threat hunting using queries, dashboards and behavioural analytics

What we offer

Up to £3,600 of free shares each year after one year of service
33 days holiday (including bank holidays) increasing to up to 38 days
Option to buy or sell up to an additional five days of annual leave
Financial & Mortgage Advice
24-Hour Ecare
Cycle to Work Scheme
Flexible Working
Simply Health
Private Health Cover
Critical Illness Cover

Fulltime

Senior Cloud Engineer

The Senior Cloud Engineer will be responsible for providing technical support to...

Location

United States , San Jose

Salary:

161760.00 - 242640.00 USD / Year

AMD

Expiration Date

Until further notice

Requirements

Bachelor's degree in Computer Science, Engineering, or a related field
Cloud Systems Engineer general experience of various CSPs fundamentals with: Terraform, YAML, Jenkins, GitHub actions
Python, Golang, Shell, Java/J2EE, NodeJS, ReactJS, HTML5, PyTorch
Able to build and support a full CI/CD pipeline to support consistent code deployment
Preferred understanding of AI framework
Managing GPU clusters optimizing GPU-based services/tools/software
Experience with Container technologies (GKE, EKS, ECS, Docker, Kubernetes) is desirable
Understanding CHANGE Management/Release Process
Strong understanding of Agile/Scrum methodologies
Strong active listening and consensus-building skills and passionate about learning and sharing knowledge with others

Job Responsibility

Design, develop, deploy, monitor, maintain, and evolve cloud-native resources, tools, services, reusable modules (infrastructure-as-code-practices) and frameworks to secure and automate provisioning of cloud infrastructure that empowers our users across Azure, AWS, GCP
Provide customers with standards and best practices on how to deploy and consume cloud-based services
Proactively seek opportunities to improve operational efficiency of teams and usage of cloud services
Contribute to a strong team-culture and an atmosphere of cross-functional teamwork
Work with internal customers in managing incident tickets to achieve operational excellence
Work with global teams to provide support and complete IT projects
Create secure hybrid deployments of virtual machines, and PaaS solutions in Azure, AWS, GCP
Work with Project teams to understand and accommodate application architecture and the App’s specific requirements for Azure, AWS, and GCP
Collaborate with other engineers and stakeholders to share knowledge and build expertise for IaaS, PaaS, and Saas deployment
Collaborate with onshore and offshore resources

Fulltime

Senior ML Engineer

We are seeking an experienced Senior ML to join our team and engage in a diverse...

Location

United Kingdom , Bath

Salary:

Not provided

BMT

Expiration Date

Until further notice

Requirements

Be a UK sole national
Have held no other nationality at any time
Have continuously resided in the United Kingdom for the past five years
Be able to obtain and maintain full UK security clearance in accordance with government vetting standards
Provide satisfactory evidence of identity, nationality, and residency as part of the clearance process
Capability to design and implement end‑to‑end ML pipelines
Ability to select, train, and tune models (classical ML and deep learning) using frameworks such as PyTorch, TensorFlow, or scikit‑learn
Experience containerising and deploying models (e.g., Docker), implement CI/CD, monitoring, drift detection, and automated retraining on Azure/AWS/GCP as appropriate
Demonstrated capability to work with data engineers to ensure high‑quality datasets, versioning, lineage, and governance
Capable of pairing with data scientists and software engineers, review code, and share best practices

Job Responsibility

Design, build, and deployment of machine‑learning systems, applying robust software engineering practices and an in‑depth understanding of model behaviour, performance, and limitations
Select, prepare, and pipeline data for model training and inference. Implements, trains, evaluates, and optimises machine‑learning models, continually improving them through iterative experimentation and additional data
Create scalable and automated ML pipelines, including feature extraction, model training, validation, packaging, deployment, and monitoring
Design and implement dashboards, diagnostics, and evaluation tooling to ensure transparency, performance tracking, and operational reliability across the ML lifecycle
Within defined delivery goals, refines prototype models into production‑ready components, contributing to development, optimisation, demonstration, and integration activities
Apply standardised engineering and evaluation methods, producing clear technical documentation and communicating design choices, performance outcomes, and limitations
Contribute to internal knowledge bases and participates in professional ML engineering communities
Ensure responsible handling of data throughout the ML lifecycle, including secure storage, access control, data lineage, versioning, and quality checks
Evaluate data integrity and suitability for ML workflows, and advises on transformations, feature representation, and schemas needed for efficient training and inference
Implement metadata standards, reproducible data pipelines, and automated validation procedures to maintain trustworthy data assets

What we offer

Private Medical (family coverage)
Enhanced Pension
18 weeks enhanced maternity pay (after a qualifying period of 1 year)
Family friendly policies
Committed to an inclusive culture
Wellbeing Fund – an annual fund for personal hobbies or interests
26 Days Annual Leave (plus bank holidays)
Holiday Trading
Retail Vouchers
Professional Subscriptions

Fulltime

Senior Applied AI Scientist

Microsoft Sentinel Platform NEXT R&D labs is the strategic incubation engine beh...

Location

United States , Multiple Locations

Salary:

119800.00 - 234700.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience
Candidates must be able to meet Microsoft, customer and/or government security screening requirements are required for this role
This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter
Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience
3+ years working with Machine Learning (ML)/Artificial Intelligence (AI) systems (e.g., Large Language Models (LLM/LRM)/Generative AI (GenAI), retrieval/Retrieval-Augmented Generation (RAG), model serving, experimentation platforms, data pipelines) including establishing evaluation metrics and improving model quality
Demonstrated success driving zero-to-one (0→1) initiatives
ML background and hands-on experience
Experience with ML lifecycle: model training, fine-tuning, evaluation, continuous monitoring, and more
Coding ability in one or more languages (e.g., Python, C#, C++, Rust, JavaScript/TypeScript)
Familiarity and previous work in the field of cybersecurity (e.g., threat detection/response, SIEM/SOAR, identity, endpoint, cloud security) and familiarity with analyst workflows

Job Responsibility

AI/ML Research: design, development, and analysis of novel AI and machine learning models and algorithms for security and enterprise-scale applications
Innovate Across Domains: Explore and apply a broad spectrum of AI/ML techniques, including deep learning, Bayesian probabilistic modeling, classical ML, generative models, and hybrid approaches
Experimentation & Evaluation: Design and execute experiments, simulations, and evaluations to validate models and system performance, ensuring measurable improvements
Collaboration: Partner with engineering, product, and research teams to translate scientific advances into robust, scalable, and production-ready solutions
Customer Impact: Engage with enterprise customers and field teams to co-design solutions, gather feedback, and iterate quickly based on real-world telemetry and outcomes

Fulltime

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Senior Machine Identity Security Engineer - AI governance

Job Description

Job Responsibility

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