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Anthropic

<div><div><h2 class="jobSectionHeader">About Anthropic</h2>

Anthropic&rsquo;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</div><div><div>
<h2 class="jobSectionHeader">
About the role</h2>

As an Applied AI team member at Anthropic, you will be a Pre-Sales architect focused on becoming a trusted technical advisor helping large enterprises understand the value of Claude and paint the vision on how they can successfully integrate and deploy Claude into their technology stack. You'll combine your deep technical expertise with customer-facing skills to architect innovative LLM solutions that address complex business challenges while maintaining our high standards for safety and reliability.

Working closely with our Sales, Product, and Engineering teams, you'll guide customers from initial technical discovery through successful deployment. You'll leverage your expertise to help customers understand Claude's capabilities, develop evals, and design scalable architectures that maximize the value of our AI systems.
<h2 class="jobSectionHeader">
Responsibilities:</h2>
<ul><li>Partner with account executives to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation</li>
<li>Serve as the primary technical advisor to enterprise customers throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams &amp; stakeholders to drive customer success</li>
<li>Support customers building with both the Claude API and Claude for Work</li>
<li>Create and deliver compelling technical content tailored to different audiences. You will need to be able to spread the gamut from technical deep dives for engineering &amp; development teams up to business value focused conversations with executives</li>
<li>Guide technical architecture decisions and help customers integrate Claude effectively into their existing technology stack</li>
<li>Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases</li>
<li>Identify common integration patterns and contribute insights back to our Product and Engineering teams</li>
<li>Travel occasionally to customer sites for workshops, technical deep dives, and relationship building</li>
<li>Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns</li>
</ul><h2 class="jobSectionHeader">You may be a good fit if you have:</h2>
<ul><li>5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager</li>
<li>Experience working with enterprise customers, navigating complex buying cycles involving multiple stakeholders</li>
<li>Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering &amp; IT teams, and more</li>
<li>Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders</li>
<li>Experience designing scalable cloud architectures and integrating with enterprise systems</li>
<li>Comfortable with python</li>
<li>Familiarity with common LLM frameworks and tools or a background in machine learning or data science</li>
<li>Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities</li>
<li>A love of teaching, mentoring, and helping others succeed</li>
<li>Excellent communication and interpersonal skills, able to convey complicated topics in easily understandable terms to a diverse set of external and internal stakeholders. You enjoy engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities</li>
<li>Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems</li>
</ul>
</div>Deadline to apply: None. Applications will be reviewed on a rolling basis.</div><div><div><div><div>
The annual compensation range for this role is listed below.

For sales roles, the range provided is the role&rsquo;s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</div></div>
Annual Salary:
&pound;190,000 - &pound;230,000 GBP</div></div><div><h2 class="jobSectionHeader">
Logistics</h2>

Minimum education: Bachelor&rsquo;s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. 
 
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links&mdash;visit anthropic.com/careers directly for confirmed position openings.
<h2 class="jobSectionHeader">
How we're different</h2>

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact &mdash; advancing our long-term goals of steerable, trustworthy AI &mdash; rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
<h2 class="jobSectionHeader">
Come work with us!</h2>

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.</div></div>

Applied AI Architect, Industries

Talan

<div>Company Description 
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). 
Job Description 
As our AI practice scales, we are seeking an experienced AI Architect / Engineer to act as the senior technical authority shaping how we design and deliver next-generation AI solutions. This is a role for someone who has moved beyond building individual models to architecting entire systems: agentic platforms, LLM-powered applications, and the production infrastructure that makes them dependable at enterprise scale.
You will sit at the intersection of strategy and delivery, operating across multiple client engagements simultaneously. In the early phases you will shape solutions, validate technical approaches, and translate ambiguous business problems into robust, deployable architectures. As engagements mature, you will provide the technical oversight that keeps delivery teams aligned to the original design intent. Your influence will be felt in pre-sales conversations, solution blueprints, and the technical standards that define how our practice builds.
This is a hands on architectural role, not a purely advisory one. We expect you to remain close to the code, to prototype where it accelerates a decision, and to set a credible technical example for the engineers and data scientists you guide.
Required skills &amp; experience:<ul><li>
Lead end-to-end solution architecture for AI and LLM-based systems, spanning data, integration, infrastructure, and deployment.</li><li>
Design agentic architectures and multi-agent orchestration patterns, defining how LLMs, tools, APIs, and retrieval layers interact reliably.</li><li>
Shape early-stage engagements (scoping, solutioning, estimation, and pre-sales) turning client ambition into deliverable technical plans.</li><li>
Provide technical validation and quality oversight across several concurrent projects, mitigating risk before it reaches delivery.</li><li>
Define LLM integration and prompting strategies, including RAG, fine-tuning, evaluation, and guardrailing approaches.</li><li>
Establish MLOps and LLMOps practices that ensure solutions are observable, testable, and production ready.</li><li>
Set architectural standards, reusable patterns, and reference implementations that raise the quality bar across the practice.</li><li>
Partner with Responsible AI colleagues to embed safety, security, and governance into solution designs from the outset.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Minimum 5 years in AI architecture or AI engineering, ideally 10+, with a track record of production deployments.</li><li>
Deep expertise in LLMs, agent frameworks (e.g. LangGraph, AutoGen, Semantic Kernel), API design, and orchestration.</li><li>
Strong cloud engineering experience.</li><li>
Proven MLOps / LLMOps capability &mdash; CI/CD for models, monitoring, evaluation, and cost optimisation.</li><li>
Hands-on software engineering background (Python and modern tooling) underpinning your architectural decisions.</li><li>
Comfort managing multiple engagements at once, with pragmatic judgement on trade-offs and delivery risk.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Experience in consulting, professional services, or pre-sales environments.</li><li>
Exposure to enterprise-scale, regulated AI deployments (financial services, public sector, healthcare).</li><li>
Familiarity with vector databases, knowledge graphs, and advanced retrieval techniques.</li><li>
Relevant cloud or AI certifications.</li></ul>
You must be:<ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul> 
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul>
Why join:
You will be a founding technical voice in a practice that is investing decisively in AI. The work is varied, intellectually demanding, and commercially significant, you will shape solutions that reach production, not slideware. You will have the autonomy to define how we build, the support of a collaborative multidisciplinary team, and a clear platform to grow into a practice-leading technical figure.</div>

AI Architect / Engineer (Agentic AI & LLM Architecture)

HCLTech

City Of London, England
 Job Summary
 
Job Title: Forward Deployed Engineer (FDE), Gemini Enterprise
 The FDE is a hybrid of a Staff Software Engineer and a Strategic Consultant. You will be the technical lead responsible for deploying Gemini Enterprise App and Gemini Enterprise Agent Platform within client environments. You will architect and code the "connective tissue" that allows Gemini agents to reason across private enterprise silos, execute long-running workflows, and adhere to strict corporate governance.
 
Key Responsibilities
 
Key Responsibilities
 <ul>
<li>Agentic Architecture: Design multi-agent systems using the Agent Development Kit (ADK), implementing patterns like hierarchical delegation and self-reflection.</li>
<li>Production Implementation: Move beyond prototypes. You will write the production code that integrates Gemini agents with legacy APIs, SQL/NoSQL databases, and ERP systems (SAP, Salesforce, etc.).</li>
<li>The "Grounding" Expert: Build and optimize RAG (Retrieval-Augmented Generation) pipelines using Vertex AI Search and BigQuery, ensuring agents have "zero-hallucination" access to enterprise truths.</li>
<li>Governance & Security: Deploy Agent Identity and Agent Gateway protocols to ensure every AI action is auditable, secure, and compliant with regional data residency laws.</li>
<li>Field-to-Product Loop: Act as the "eyes and ears" for Google’s core engineering. Identify common friction points in the Agent Platform and collaborate with product teams to build reusable "Skills" and modules.</li>
</ul>
Skill Requirements
 
Technical Requirements
 Domain Stack Expertise
 AI/ML Platform Gemini 3.0, Gemini Enterprise Agent Platform, Agent Studio, Vertex AI
 Engineering Python (Advanced), Go or Java, TypeScript, REST/gRPC APIs
 Data Architecture BigQuery, Vector Search, AlloyDB, Apache Beam / Dataflow
 Orchestration Agent Development Kit (ADK), LangGraph-native patterns, Kubernetes (GKE)
 Ops & Eval Agent Evaluation (Auto-SxS), Agent Observability, CI/CD for LLMs
 
#body.unify div.unify-button-container .unify-apply-now: focus, #body.unify div.unify-button-container .unify-apply-#body.unify div.unify-button-container .unify-apply-now: focus, #body.unify div.unify-button-container .unify-apply-

AI Solution Architect I

<div><div><h2 class="jobSectionHeader">About Anthropic</h2>

Anthropic&rsquo;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</div><div>
About the role:

As an Applied AI Security Architect, you will serve as Anthropic's trusted security expert for our most demanding enterprise customers. You'll engage directly with CISOs, security architects, compliance officers, and technical leaders at the largest financial institutions, insurers, and other highly regulated enterprises across EMEA to address their most critical questions about deploying Claude safely and securely &mdash; including the security capabilities of our latest generations of Claude models.

This is a pre-sales technical role focused on security, compliance, networking, and data architecture. Your job is to walk into a room full of security professionals and demonstrate deep expertise in enterprise security, regulatory compliance, and data protection.

Whether you've been a Security Architect, Solutions Architect, Field CTO, or senior pre-sales engineer, what matters is that you understand how large European institutions evaluate and adopt technology, and can speak credibly to their security and compliance concerns. This is a senior role: you will own our most complex and escalated security conversations in the region, often as the decisive technical voice in front of a CISO.

We are looking for someone excited to help define how European enterprises should think about security and compliance in the age of AI. How do MCP, autonomous agents, and RBAC work together? How do you deploy frontier models in line with GDPR, EU data residency, and the EU AI Act? If working at the intersection of AI adoption and regulated industries excites you, this is the role for you.

Responsibilities:
<ul>
<li>Serve as the primary security and compliance expert in customer engagements, addressing technical questions about Claude's architecture, data flows, encryption, access controls, and deployment models.</li>
<li>Partner with CISOs, security architects, compliance teams, and DPOs to understand their security requirements and design solutions that meet European regulatory standards (GDPR, EU AI Act, DORA, NIS2, SOC 2, PCI-DSS, and national regulator expectations).</li>
<li>Lead technical deep-dives on network architecture, EU data residency, data retention and Zero Data Retention (ZDR) policies, cross-border data transfers, API security, authentication/authorization, audit logging, and integration patterns for regulated environments.</li>
<li>Support enterprise security reviews, vendor assessments, and due diligence with detailed technical documentation and expert guidance.</li>
<li>Guide customers through EU AI Act readiness, DORA, and NIS2, and position Anthropic within the European competitive landscape.</li>
<li>Collaborate with Sales and Applied AI teams from initial conversations through deployment.</li>
<li>Partner closely with Anthropic&rsquo;s product and engineering teams to understand Claude's security capabilities, relay customer feedback, and influence the roadmap.</li>
<li>Develop security-focused collateral, reference architectures, and best practices for regulated industries.</li>
<li>Travel regularly across EMEA for security workshops, architecture reviews, and strategic account meetings.</li>
</ul>
You may be a good fit if you have:
<ul>
<li>7+ years of experience in enterprise security, cloud architecture, or technical pre-sales, with significant exposure to regulated industries in EMEA (financial services, insurance, healthcare).</li>
<li>Deep technical knowledge of enterprise security concepts: network security, identity and access management, encryption (at rest and in transit), API security, and audit/logging requirements.</li>
<li>Deep working knowledge of GDPR (data residency, data retention and Zero Data Retention, international transfers, DPIAs) and strong familiarity with the EU AI Act as it applies to foundation models.</li>
<li>Experience navigating compliance frameworks relevant to European financial services and insurance (DORA, NIS2, SOC 2, PCI-DSS, and national regulators' guidance on AI/ML such as FCA/PRA, BaFin, ACPR, FINMA).</li>
<li>A track record of leading complex, high-stakes engagements with CISOs, security teams, and compliance officers at large European enterprises.</li>
<li>Strong understanding of cloud architecture and deployment models (AWS, Azure, GCP), including VPCs, private endpoints, hybrid connectivity, and the European sovereign cloud landscape.</li>
<li>Excellent communication skills: able to explain complex security topics to technical and non-technical audiences.</li>
<li>Fluent English; additional European languages are a strong plus.</li>
<li>A good understanding of the EMEA enterprise AI market and competitive landscape.</li>
<li>The ability to navigate ambiguity and move fast in a rapidly evolving market.</li>
<li>A collaborative mindset: sales at Anthropic is a team sport.</li>
<li>Excitement about AI's potential to transform highly regulated industries, and a genuine desire to help customers adopt it safely and responsibly.</li>
</ul></div><div><div><div><div>
The annual compensation range for this role is listed below.

For sales roles, the range provided is the role&rsquo;s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</div></div>
Annual Salary:
&pound;190,000 - &pound;230,000 GBP</div></div><div><h2 class="jobSectionHeader">
Logistics</h2>

Minimum education: Bachelor&rsquo;s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. 
 
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links&mdash;visit anthropic.com/careers directly for confirmed position openings.
<h2 class="jobSectionHeader">
How we're different</h2>

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact &mdash; advancing our long-term goals of steerable, trustworthy AI &mdash; rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
<h2 class="jobSectionHeader">
Come work with us!</h2>

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.</div></div>

Applied AI Security Architect

<div>Company Description 
IFS is a billion-dollar revenue company with 6000+ employees on all continents. Our leading AI technology is the backbone of our award-winning enterprise software solutions, enabling our customers to be their best when it really matters&ndash;at the Moment of Service&trade;. Our commitment to internal AI adoption has allowed us to stay at the forefront of technological advancements, ensuring our colleagues can unlock their creativity and productivity, and our solutions are always cutting-edge.
At IFS, we&rsquo;re flexible, we&rsquo;re innovative, and we&rsquo;re focused not only on how we can engage with our customers but also on how we can make a real change and have a worldwide impact. We help solve some of society&rsquo;s greatest challenges, fostering a better future through our agility, collaboration, and trust.
We celebrate diversity and understand our responsibility to reflect the diverse world we work in. We are committed to promoting an inclusive workforce that fully represents the many different cultures, backgrounds, and viewpoints of our customers, our partners, and our communities. As a truly international company serving people from around the globe, we realize that our success is tantamount to the respect we have for those different points of view.
By joining our team, you will have the opportunity to be part of a global, diverse environment; you will be joining a winning team with a commitment to sustainability; and a company where we get things done so that you can make a positive impact on the world.
We&rsquo;re looking for innovative and original thinkers to work in an environment where you can #MakeYourMoment so that we can help others make theirs. With the power of our AI-driven solutions, we empower our team to change the status quo and make a real difference.
If you want to change the status quo, we&rsquo;ll help you make your moment. Join Team Purple. Join IFS. 
Job Description 
As a Solution Architect &ndash; ERP / EAM, you sit at the intersection of product strategy, deep solution knowledge, and real-world customer process understanding. You are part of a small, high-calibre team whose purpose is to accelerate IFS's ability to deliver meaningful value through AI, agentic capabilities, and digital workers &ndash; embedded directly into ERP and EAM workflows.
This is not a generic presales or product management role. It is a specialist position designed for individuals who understand IFS ERP and EAM at depth: down to the business process, down to the sub-process, and in many cases down to the functional object, data model, or workflow component level. You will use that knowledge to identify where emerging IFS capabilities &ndash; including IFS Loops, digital workers, and the IFS agentic AI platform &ndash; can generate real, verifiable customer value.
Role Description 
This role requires a senior individual contributor who operates across product, engineering, sales, and customer conversations. The primary alignment sits within the IFS product organisation, with a close working relationship to R&amp;D and a dotted-line into sales and go-to-market.
The role requires fluency in both the language of engineering and product, as well as in customer outcomes and commercial opportunity. The individual will help shape what gets built, validate whether it works, and communicate what it means&mdash;to internal stakeholders and to customers alike.
In short, this role exists to ensure that IFS's most advanced ERP and EAM capabilities are delivered into the right contexts, in the right way, with the right supporting evidence.
Operating Model &amp; Time Allocation
This role operates across four primary dimensions. The split below reflects a realistic working rhythm, though the balance will shift based on business cycle and opportunity:
30%: Customer-facing support &ndash; active opportunities, strategic conversations, and 'what next' engagements with key accounts.
30%: Product organisation collaboration &ndash; process mapping, solution design, and Loops / digital worker opportunity identification within ERP and EAM.
20%: Engineering engagement &ndash; validation, feasibility assessment, and pre-release pressure-testing of proposed capabilities.
20%: Research, self-development, and internal enablement &ndash; staying current with IFS platform direction, ERP/EAM domain trends, and Industrial AI advances.
Ideal Candidate Profile<ul><li>
IFS ERP Portfolio Depth (Mandatory): Candidates must demonstrate genuine, hands-on depth across the IFS ERP portfolio. This is a non-negotiable requirement. Experience across core IFS ERP functional areas &ndash; including financials, supply chain, manufacturing, procurement, and project-based operations &ndash; is expected, whether gained as an IFS employee, IFS partner professional, or in a customer-side implementation role.</li><li>
IFS Cloud / IFS Applications Experience: Practical working experience with IFS Cloud and/or IFS Applications, with the ability to operate at functional and process level, not simply at a conceptual overview.</li><li>
ERP &amp; EAM Process Fluency: Demonstrable ability to work at the level of detailed business processes and sub-processes in ERP and EAM environments. Understanding of how these processes connect, depend on each other, and create operational outcomes.</li><li>
IFS EAM Familiarity: Strong working knowledge of IFS EAM-related capabilities is highly desirable. Candidates who can operate across both ERP and EAM process domains are strongly preferred.</li><li>
AI &amp; Automation Orientation: Genuine curiosity and working understanding of how AI, agentic capabilities, and workflow automation tools can be applied inside complex enterprise processes. Ability to identify opportunity areas and assess their practical viability.</li><li>
Cross-Functional Credibility: Proven ability to work effectively with product managers, engineers, sales leaders, and senior customer stakeholders. Comfortable challenging assumptions and bringing clarity to ambiguous situations.</li><li>
Communication &amp; Articulation: Ability to communicate complex product and process concepts clearly, credibly, and concisely &ndash; to both technical and non-technical audiences.</li></ul> 

Qualifications<div> 
Essential: 
<ul><li>University degree, or equivalent professional qualifications.</li><li>Extensive experience of implementation projects, working directly with customers.</li><li>In conjunction with a Project Manager, involvement in the planning and resourcing of a</li></ul>
project, taking a lead role in managing and guiding the consulting team on all solution 
related matters. 
<ul><li>Experience in working with C-Level customer stakeholders.</li><li>Excellent communication skills.</li><li>Lead role in the development of the ERP solution.</li></ul></div></div>

AI Solution Architect – ERP / EAM

Accenture

<div>YOU ARE
As an experienced and senior AI/LLM Architect, you will play a pivotal in designing and delivering end-to-end AI platform architectures that power the modern, reinvented enterprise. Operating at the intersection of business and engineering, you will own the technical design of advanced AI systems &mdash; spanning classical machine learning, generative AI, and agentic systems &mdash; ensuring they are purposefully architected to meet client business objectives and enterprise-grade standards.
Within this scope, you will take deep ownership of one or more critical architecture domains &mdash; such as agentic application design, AI security and trust, AI operations and observability, data and knowledge engineering, or model platforms and inference &mdash; serving as the lead authority in your domain across client engagements. You will develop and maintain specialized expertise in the technologies, patterns, and emerging practices within your domain, bringing that depth to bear in shaping architecture decisions, accelerating delivery, and building reusable assets that extend across the practice. You will evaluate, select, and apply the right design patterns, technical frameworks, and tools within your domain and across the broader AI architecture &mdash; ensuring cohesion across the full system. This includes architecting AI agents encompassing multi-agent orchestration, tool use, skills use, and memory systems, as well as the integration of fine-tuned foundation models and classical ML models into scalable, production-ready platforms.
A critical dimension of this is owning the design of a comprehensive AI context layer &mdash; drawing on enterprise knowledge bases, structured and unstructured data sources, and domain-specific content &mdash; to ground AI systems in the realities of each client's business and ensure outputs are accurate, trustworthy, and impactful. As the technical authority on your domains, you will lead architecture decisions and be accountable for ensuring systems meet rigorous non-functional requirements across security, observability, governance, performance, and scalability. You will produce and own the architecture artifacts that shape delivery &mdash; including architecture decision records (ADRs), component and data flow diagrams, and integration specifications &mdash; and provide the technical leadership that enables cross-functional teams of data engineers, ML engineers, and application developers to execute with clarity and confidence.
Your contributions will be instrumental in shaping how clients adopt and scale AI, pushing the boundaries of what these systems can achieve and delivering measurable, lasting business value.
THE WORK<ul><li>
Translate business strategy into a technical vision by defining the non-functional requirements (NFRs) necessary to meet operational goals for performance, reliability, and cost.</li><li>
Lead stakeholder workshops to align on technical feasibility, define project scope, and manage expectations with clients and leadership.</li><li>
Drive the technology selection process, evaluating build-vs-buy decisions for AI platforms (e.g., Arize, LangSmith) and foundational models.</li><li>
Architect model- and tool-agnostic multi-agent systems governed by an MCP Control Plane.</li><li>
Design and implement the Agent Registry as the mandatory system of record and the AI Gateway for runtime policy enforcement.</li><li>
Design and implement a certification gate to ensure no uncertified agents enter production, validating identity, policies, and evaluation metrics.</li><li>
Design, implement, and abstract core agent services, including a first-class abstracted memory service with semantic, episodic, and procedural endpoints.</li><li>
Architect the end-to-end data pipeline for AI systems, including data ingestion, preprocessing, and synchronization for fine-tuning and RAG.</li><li>
Design and implement the context layer&mdash;spanning knowledge graphs, vector search, and semantic retrieval&mdash;to create reliable, grounded RAG pipelines.</li><li>
Architect foundation model adaptation strategies, including dynamic, cost-and-performance-aware model routing and selection.</li><li>
Design, implement, and prototype high-throughput, low-latency inferencing solutions using techniques like response caching and request batching.</li><li>
Define security, governance, and observability as centrally-enforced, by-design controls for all AI systems.</li><li>
Architect a robust, defense-in-depth security framework, including per-agent identity with IAM/IAP binding and layered guardrails.</li><li>
Design and implement FinOps controls enforced at the AI Gateway, including token budgets, cost-center labeling, and threshold alerts.</li><li>
Establish the framework for comprehensive system evaluation, adopting productized tools and instrumenting observability with OTel</li><li>
Define and maintain the enterprise-wide AI reference architecture, reusable design patterns, and a library of approved software components.</li><li>
Independently design, implement, build, and deliver proof-of-concept prototypes and foundational software components to validate architectural decisions.</li><li>
Produce and own authoritative architecture artifacts, including blueprints, sequence diagrams, design specifications, and Architectural Decision Records (ADRs).</li><li>
Mentor and guide cross-functional engineering teams (data, ML, application) on architectural best practices and design patterns.</li><li>
Continuously research and integrate emerging AI patterns, frameworks, and technologies to maintain a forward-looking architecture.</li></ul></div>
 
<div>EDUCATION<ul><li>
Bachelor's Degree or equivalent</li></ul>
BASIC (REQUIRED) QUALIFICATION<ul><li>
Experience in designing &amp; deploying enterprise grade advanced AI solutions using agentic, generative and classical AI/ML using at least one cloud vendor.</li><li>
Experience in the Agentic, LLM and Generative AI space.</li><li>
Coding experience using Python</li><li>
Experience architecting and operationalizing LLM driven application architecture patterns.</li><li>
Expertise in coding engineering, machine learning, deep learning and NLP solutions and applications.</li><li>
Experience as a machine learning architect in the industry designing big data, machine learning. large scale analytical engineering solutions.</li></ul></div>

AI LLM Technology Architecture Manager

<div>YOU ARE
As a hands-on AI/LLM Architect, you will be at the heart of designing and building advanced AI systems that power the modern enterprise. This is a deeply technical, hands-on &mdash; you will spend the majority of your time in the architecture and engineering of real-world AI solutions across classical machine learning, generative AI, and agentic systems, delivering these within active client engagements.
You will translate requirements into concrete architecture decisions: selecting design patterns, evaluating and benchmarking technical frameworks, assembling reusable components, and making deliberate technology choices that balance innovation with enterprise-grade reliability. You will design and build AI agent architectures &mdash; including multi-agent orchestration, tool use, skills use, and memory systems &mdash; and work hands-on with foundation models through fine-tuning, retrieval-augmented generation (RAG), and custom model integration.
A part of your work will also involve engineering the AI context layer that makes these systems intelligent in practice &mdash; connecting enterprise knowledge bases, structured and unstructured data sources, and domain-specific content so that AI outputs are grounded, accurate, and relevant to the client's business.
You will design and validate systems against enterprise non-functional requirements across security, observability, governance, performance, and scalability.
A core output of this is the production of tangible engineering and architecture deliverables. This means writing and owning software components &mdash; building, integrating, and testing AI system modules as a practitioner &mdash; alongside producing detailed architecture artifacts including architecture decision records (ADRs), component diagrams, data flow diagrams, and integration specifications that guide and enable broader engineering teams.
You will work with cross-functional delivery teams alongside data engineers, ML engineers, and application developers, and this is an opportunity to develop deep expertise across the full AI architecture stack, sharpen your engineering instincts on complex, real-world problems, and build a foundation for growing into a lead or principal architect over time.
THE WORK<ul><li>
Independently design, build, and deliver software components across the AI architecture &mdash; owning them end to end from design through implementation, integration, and testing as a hands-on practitioner</li><li>
Design and build AI agent architectures &mdash; including individual agents, their prompts, tools, and skills, multi-agent orchestration, and memory systems &mdash; making deliberate design pattern and technology choices</li><li>
Design and implement agent orchestration patterns that handle task handoffs, communication, state management, and error recovery, validating them through hands-on prototyping</li><li>
Evaluate multiple design options and technical approaches, making deliberate, justified design choices that balance capability, cost efficiency, performance, and enterprise-grade reliability</li><li>
Design, build, and run evaluation strategies and harnesses that measure agent and system quality on metrics such as accuracy, relevance, and faithfulness, translating findings into design improvements</li><li>
Architect and implement foundation model integrations &mdash; selecting the right models, invocation patterns, and customization approaches (fine-tuning, RAG, custom integration) based on capability, cost, and performance trade-offs</li><li>
Design and build model adaptation and fine-tuning pipelines, applying working knowledge of transformer-based architectures to inform model selection and optimization</li><li>
Design and build the AI context layer &mdash; including context graph design and ingestion pipelines that parse, chunk, enrich, and index structured and unstructured enterprise content, and the retrieval components that ground AI outputs in the client's knowledge</li><li>
Build embedding, vector storage, and retrieval (semantic, hybrid, reranking) into end-to-end RAG pipelines, applying integration patterns that connect to enterprise data sources</li><li>
Design and implement context assembly and memory components that manage prompts, context windows, and conversational state for grounded, accurate outputs</li><li>
Identify, design, and build reusable components and solution patterns that accelerate delivery and can be templated across engagements</li><li>
Design for cost efficiency and performance &mdash; optimizing model usage, inference patterns, caching, and resource utilization to meet target latency, throughput, and cost objectives</li><li>
Design, build, and validate systems against enterprise non-functional requirements &mdash; implementing guardrails, prompt-injection defenses, PII handling, and access controls for security and Responsible AI</li><li>
Build governance controls including versioning, audit logging, and lineage tracking, and produce the model documentation that keeps systems auditable</li><li>
Build observability into systems &mdash; logging, tracing, monitoring, alerting, and cost tracking &mdash; to ensure AI solutions remain healthy, performant, and scalable in production</li><li>
Produce detailed architecture artifacts &mdash; including architecture decision records (ADRs), architecture blueprints, design documents, agent orchestration and integration pattern specifications, component and data flow diagrams &mdash; that guide and enable broader engineering teams</li><li>
Continuously learn, evaluate, and apply new design patterns, frameworks, and technologies across the fast-evolving AI landscape, balancing innovation with enterprise-grade reliability</li><li>
Collaborate with cross-functional delivery teams &mdash; data engineers, ML engineers, and application developers &mdash; to translate requirements into concrete architecture decisions that meet stakeholder needs</li></ul></div>
 
<div>EDUCATION<ul><li>
Bachelor's Degree or equivalent</li></ul>
BASIC (REQUIRED) QUALIFICATION<ul><li>
Experience in designing &amp; deploying AI / ML solutions using at least one cloud vendor as an AI/ML architect.</li><li>
Experience in the Agentic, LLM and Generative AI space.</li><li>
Experience architecting and operationalizing LLM driven application architecture patterns.</li><li>
Expertise in coding with Python and engineering, machine learning, deep learning and NLP solutions and applications.</li></ul></div>

AI LLM Technology Architecture Assoc Manager

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