Why Dialpad

Dialpad’s Agentic AI platform turns conversations into autonomous workflows that drive revenue, efficiency, and unforgettable customer experiences. Fortune 1000 companies trust our AI Voice & Digital Agents to resolve millions of interactions every day. We’re scaling fast and need Forward Deployed Engineers who want to be at the intersection of innovation and business impact.

Your Role

The primary purpose of our Forward Deployed Engineering team is to accelerate the adoption and realization of value from our AI platform by embedding within our most strategic customer accounts. You will be the crucial link that translates complex business challenges into production ready, high-impact Agentic AI systems, driving business outcomes. FDE’s will act as the company's most technically fluent business consultant and the customer's most trusted AI architects. 

What We Do

• Business Translation and Discovery: Rapidly embed with customer stakeholders and operational leaders to deeply understand their most complex, high-stakes business problems. Translate ambiguous business objectives into clear, shippable Agentic AI-powered solutions.

• The Go-To-Market Bridge: Partner directly with our Sales, Sales Engineers, Professional Services and Customer Success teams to serve as the deep technical authority during critical pre-sales evaluations and post-sales deployments. You don't just sell the vision, you build the capability that validates the investment.

• Product Alignment and Influence: Capture common customer pain points, successful integration patterns, and platform limitations discovered in the field. Synthesize and deliver this critical, high-value signal directly back to our core Product and Engineering teams to influence the product roadmap and accelerate feature development.

• AI Envisioning: Navigate complex enterprise infrastructure (cloud, on-prem, data pipelines) to integrate our platform. Guide customers on production grade Agentic bot builds and integration to custom data connectors, orchestration logic, and full-stack systems that bring AI to life.

• Agentic AI Design: Design and deploy complex multi-agent systems, architectures, and fine-tuned models tailored to the customer's unique data, domain, and security requirements. Author multi‑step prompts, retrieval pipelines, and decision logic that plug into CRMs, ERPs, and custom APIs via our MCP framework.

About You

• 4+ years of experience in a high-impact, customer-facing technical role such as Forward Deployed Engineering, Technical Consulting, high touch Sales Engineering or Solutions Architecture, or technical consulting for SaaS/AI products.

• Deep, demonstrable expertise in the modern AI/ML stack: LLMs, Generative AI concepts, vector databases, and agent orchestration frameworks. Proficiency in Python, Go, JS/TS plus hands‑on experience with LLM frameworks.

• Unrivaled Business Acumen: The ability to simplify technical complexity and communicate clear trade-offs, value propositions, and project plans to both a core engineering team and a non-technical C-suite executive.

• You thrive in ambiguity, take full ownership of outcomes, and are driven by delivering tangible, measurable results for the customer, often working under tight timelines.

• Contributor to a dynamic team culture, focused on high growth industry innovation, team collaboration, customer success, and having fun!

• Business-level fluency in Japanese and English required. 

Bonus Points

• Telephony stack knowledge (WebRTC, SIP, SBCs).

• Experience deploying chatbots or voice bots at >10K daily conversations.

• Contributions to open‑source AI agent frameworks.

How We Work

Our values mirror those of top forward‑deployed orgs: Customer First, Relentless Momentum, Extreme Ownership, and One Team. We ship, learn, and iterate - fast.

Location: Looking for Japanese citizens / visa holders, fluent in Japanese, willing to stay in Madrid for 12 months before having the view to relocate to Tokyo. Customer base will be in Japan, involving travel to meet clients in person.

The Team

As an Associate AI Applied Engineer, you are part of our Value Engineering team and are the trusted advisor for customers working on the intersection of technology and business. As a so-called Value Engineer (VE), you partner with sales and customers to create compelling and innovative technical solutions to critical business problems leveraging cutting edge (AI) capabilities within our Celonis Process Intelligence Platform. A great VE understands the customer, the technology, and the sales cycle making it what may be the most interesting, challenging, and fulfilling role in Enterprise Software

You will be joining the Global VE Center of Excellence which is an international, diverse, and dynamic organization at the core of the Celonis Value Engineering team supporting our local field teams. As a team, we enjoy working in a fast-paced environment and share a sense of belonging to a community that wants to learn and grow together. The team culture is one based on building trust, continuous development, and improvement through coaching & mentoring. 

The Role

Talented individuals launch their careers in the enterprise software world by joining the Orbit Graduate Program as an Associate Value Engineer.

The 12-month program is a unique experience to fast start your career in the SaaS Industry that highlights hands-on learning, mentorship, and a team culture where we rely on each other to learn, grow and achieve. The program is designed to develop essential VE skills & competencies and establish strong lasting relationships allowing you to grow your career at Celonis. 

Your journey will start with onboarding & enablement to develop your business and Celonis skills through a combination of hands-on experience in customer engagements and different pieces of training which cover amongst others the Celonis Process Intelligence, domain knowledge, presentation & demo skills, discovery & objection handling as well as value selling. 

The work you’ll do:

• Work as part of the Global VE CoE to support the Japan Value Engineering team on customer engagements
• Collaborate with customers to uncover their core business challenges and determine how Celonis Process Intelligence can help them achieve their business objectives and AI Strategy
• Execute proof projects showcasing the value of Celonis Process Intelligence, frame a quantitative business value and deliver presentations to senior executives to drive investment decisions
• Prototype and develop AI solutions tailored to customer needs, including both traditional machine learning, LLM-based solutions and orchestration technology
• Drive change management and value realisation and ensure a positive return on investment
• Build strong relationships with our customers by winning their trust through technical, product expertise, and business acumen to act as a trusted advisor
• Collaborate and share customer insights & feedback with internal Product and Engineering teams to influence and co-develop (AI) product innovations
• Create re-usable collateral, best practices & tools within the Global VE Center of Excellence and feed them back to the regional Value Engineering team
• Travel to the Japan region to meet clients in person to ensure the success of customer engagements

The qualifications you need:

We are looking for people who enjoy solving problems, think outside the box, and are not afraid to make and learn from mistakes. In particular, we seek “builders” who thrive in fast-paced environments and can rapidly develop solutions and pilots using our platform and AI technologies.

You have a bachelors and/or masters degree in (Industrial) Engineering, Computer Science, Data Science / Business Analytics, AI/ML, Mathematics or other related fields, as well as valuable work/internship experience. You’re curious, self-motivated, enjoy continuous learning, and you want to work in a lively environment characterized by high growth.

You are successful as a Value Engineer if you:

• Have a passion for technology, data and AI and the impact it can have on the world
• Have a hunger to learn new technologies and bring at least basic knowledge or hands-on experience in SQL and/or Python
• Any exposure to process mining principles and completion of Celonis "Rising Star" modules would be a welcome indicator of your eagerness to develop in this field
• Are able to think analytically and creatively, especially in applying technology solutions to core business problems
• Are focused on creating and adding value for customers
• Have an entrepreneurial mindset and the ability to multi-task, prioritize and execute
• Are able to build relationships with senior management and influence decision-makers
• Are confident to present to C-level executives and larger audiences
• Are willing to travel to the Japan region to meet clients in person
• Are an effective communicator and fluent in English and Japanese

This role requires a strong blend of technical expertise, customer-facing acumen, and solution-oriented problem solving. The Data AS Consultant will work closely with Sales & Account Managers to provide technical leadership and solution design for highly consultative enterprise projects. It is a revenue-generating pre-sales position focused on enabling technical adoption and driving customer success for both new and expansion opportunities.

This role reports directly to the Team Manager, DSI, with a dotted line to the Regional Head of Japan.

Responsibilities

Technical Consultation & Solution Design

• Serve as a trusted technical advisor to enterprise customers, translating business goals into scalable, production-grade technical architectures.
  
  
• Design and document data integration architectures leveraging Similarweb’s APIs, DaaS feeds, and platform products to meet enterprise data requirements.
  
  
• Architect end-to-end data delivery pipelines into client ecosystems (e.g., Snowflake, Databricks, S3, or Google Cloud Platform).
  
  
• Provide technical workshops and POCs, guiding clients on ingestion, normalization, and querying best practices.
  
  
• Develop Statements of Work (SOWs), technical proposals, and detailed integration documentation to accelerate collaboration between internal teams and customers.
  
  

Technical Skill Execution Examples

1. Integration & Data Delivery
   
   
• Role: Design and implement integration workflows delivering Similarweb’s data via API, S3, Snowflake, or GCP Storage, tailored to customer infrastructure.
  
  
• Technical Skills:
  
  
• Advanced SQL querying and performance tuning in Databricks / Snowflake
  
  
• Proficiency with data file formats (CSV, JSON, Parquet, Delta) and understanding the trade-offs between performance, compression, and schema evolution
  
  
• Strong knowledge of ETL design, data governance, and access control
  
  
• Outcome: Clients understand technical feasibility and best practices for incorporating Similarweb data into their analytical stack.
  
  
2. Data Quality, Coverage, and Scalability
   
   
• Role: Explain how data is collected, validated, deduplicated, and scaled across geographies and verticals, referencing internal reruns and benchmarks.
  
  
• Technical Skills: Understanding of data validation, sampling frameworks, distributed storage performance, and data versioning (e.g., Delta Lake advantages).
  
  
• Outcome: Clients gain trust in data quality and scalability across enterprise-grade analytics environments.
  
  
3. Data Sampling & Proof-of-Concept Delivery
   
   
• Role: Generate and deliver custom data samples aligned with client use cases, whether via API queries, Parquet exports, Delta tables, or CSV snapshots.
  
  
• Technical Skills:
  
  
• Hands-on data extraction and transformation using SQL and Python
  
  
• Preparing data in optimal formats (e.g., Parquet v Delta)
  
  
• Managing delivery through multiple mechanisms: secure S3 share, Snowflake Data Share, API endpoints, or CSV download portals.
  
  
• Outcome: Clients can validate data structure, schema, and use-case fit before full-scale adoption.
  
  
4. Use Case Customization & Advanced Analytics
   
   
• Role: Demonstrate how Similarweb data can be enriched with client datasets (POS, CRM, or loyalty).
  
  
• Technical Skills: SQL and Python for data joins, REST and GraphQL APIs, JSON schema design, and familiarity with Model Context Protocol (MCP) for LLM integrations.
  
  
• Outcome: The client sees practical, technically sound pathways to integrating Similarweb data into their own analytical models and AI workflows.
  
  

Collaboration with Sales & Customer Teams

• Partner with Enterprise Sales Managers to qualify and design technical solutions during the sales process.
  
  
• Work with Enterprise Account Managers to drive expansion and deepen platform adoption through technical enablement.
  
  
• Collaborate closely with Customer Success and Delivery teams to ensure smooth technical transitions from pre-sales to production.
  
  
• Create reusable demos, templates, and data delivery playbooks for use across GCR teams.
  
  
• Participate in strategic account planning and contribute feedback to product and data engineering based on customer needs.
  
  

Market & Product Expertise

• Stay up to date with AI/LLM data standards, data engineering best practices, and cloud-native architectures.
  
  
• Provide feedback to product and data engineering on API performance, schema design, and data format optimization.
  
  
• Maintain familiarity with Model Context Protocol (MCP), OpenAPI, and emerging standards for data interoperability and contextual AI integrations.
  
  

Project Support & Technical Governance

• Lead technical scoping and architecture reviews during the pre-sales phase.
  
  
• Oversee sample generation, performance validation, and schema testing.
  
  
• Provide escalation support on data performance, pipeline reliability, and delivery troubleshooting.
  
  
• Ensure solutions align with data security, privacy, and compliance best practices.
  
  

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field.
  
  
• 5+ years in pre-sales, solution architecture, or data consulting, with a strong focus on technical delivery.
• Technical Expertise:
  
  
• Data Architecture & Integration: Deep understanding of cloud ecosystems (AWS, Azure, GCP) and data warehousing frameworks (Snowflake, Databricks, Redshift).
  
  
• SQL & Data Modeling: Strong query and optimization skills for data analysis and transformation.
  
  
• APIs & Data Exchange: REST and GraphQL API fluency, JSON schema design, authentication (OAuth 2.0, JWT).
  
  
• File Formats: Deep understanding of CSV, JSON, Parquet, and Delta file formats—knowing when to use each for efficiency, scalability, or incremental updates.
  
  
• Data Sample Delivery: Ability to create, test, and deliver sample datasets across APIs, S3, and warehouse sharing mechanisms.
  
  
• MCP & AI Integrations: Awareness of Model Context Protocol, LLM context injection, and structured data retrieval patterns.
  
  
• Proven experience translating business requirements into technical solutions for large enterprise data ecosystems.
  
  
• Excellent communication and presentation skills—able to bridge the gap between technical and commercial teams.
  
  
• Fluent in Japanese and English (written and spoken) with experience serving enterprise clients.
• Strong problem-solving, self-management, and team collaboration skills.

• Solve interesting, technically complex cases for Vercel customers.
• Troubleshoot issues alongside Engineering; identify and drive fixes and mitigations.
• Partner with Product, Solutions, and Customer Success to provide guidance internally and externally.
• Develop and improve internal tools and scripts that increase team efficiency.
• Specialize in a few product areas (CDN, AI enablement) and act as a domain owner within the team.
• Improve existing documentation and create new runbooks, guides, and internal processes.
• Assist Customer Success Managers with Enterprise requests and escalations.

• Domains, DNS, and SSL/TLS lifecycle management
• Caching strategy and cache-invalidation patterns
• Cloud/edge networking fundamentals and routing rules/redirects
  • Performance tuning, logs/analytics, and WAF/DDoS understanding

• SSO / SAML configuration and troubleshooting
• Experience supporting observability products
• Logging navigation and troubleshooting 
• RBAC 

• Have frontend development experience (e.g., React/Next.js).
• Enjoy technical writing for public docs or developer education.
• Have experience automating workflows with agentic services.

About Appier

Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.

The Impact You’ll Make at Appier 

We’re looking for a Staff/Senior Machine Learning Platform Engineer to join our Machine Learning Platform Team, which powers end-to-end infrastructure for model training, evaluation, deployment, and monitoring at scale. Our platform supports daily execution of hundreds of ML models and processes billions of data records across batch and streaming pipelines.
In this role, you’ll shape the architecture and core components of our ML platform—covering batch (Spark), streaming (Flink), job orchestration (Argo on Kubernetes), and infrastructure tools—while ensuring the platform remains robust, scalable, and developer-friendly. You’ll also champion best practices and modern development tools including LLM-based programming assistants.

What You’ll Work On

• Architect, implement, and scale batch (Spark) and streaming (Flink) pipelines that process billions of records daily for ML training and evaluation.
• Design and operate robust ML job execution frameworks for training, inference, and post-processing.
• Build and maintain internal API servers and developer tools to orchestrate ML jobs on Kubernetes (via Argo Workflows, Helm, Terraform).
• Design and monitor data infrastructure using ClickHouse and PostgreSQL.
• Ensure high availability and observability through monitoring tools like Prometheus and Grafana.
• Collaborate with data scientists, product managers, and engineers to deliver reliable and efficient ML platform capabilities.
• Actively adopt and promote the use of LLM-based tools (e.g., GitHub Copilot, ChatGPT) to accelerate development, documentation, and debugging.
• Mentor junior engineers and help evolve team engineering culture and standards.

What We’re Looking For

• Bachelor’s degree in Computer Science, Engineering, or a related field; Master’s preferred.
• 4+ years of hands-on experience in data systems, machine learning infrastructure, or platform engineering.
• Strong coding proficiency in Python and/or Java, with experience building large-scale production systems.
• Practical experience with Spark, Flink, Kubernetes (GKE), and infrastructure-as-code tools such as Terraform and Helm.
• Experience managing high-throughput data infrastructure using ClickHouse, PostgreSQL, or similar systems.
• Deep understanding of ML pipelines and distributed job execution in production environments.
• Proven ability to apply LLM-based tools (claude code, codex) to boost engineering productivity.
• Strong ownership, architectural thinking, and ability to lead cross-functional platform projects.

#LI-AK1

About the role

As a member of the Applied AI team at Anthropic, you will be a technical Product Engineer focused on becoming a trusted technical advisor to customers as they adopt Claude. You will work closely with customer product and engineering teams as they ship new products powered by Claude: advising on architecture design decisions, developing evaluation frameworks, and guiding customers through the most cutting edge implementation patterns for LLMs.

Working closely with our Sales, Product, and Engineering teams, you'll guide customers from technical discovery through successful deployment. You'll combine deep engineering expertise with customer-facing skills to help customers understand the potential of working with LLMs and build innovative solutions that address complex business challenges while maintaining our high standards for safety and reliability. 

Responsibilities

• Serve as a technical advisor to Anthropic customers as they deploy new products & workflows with our models: from discovery through deployment, coordinating internally across multiple teams to drive customer success

• Partner with account executives to deeply understand customer product requirements and architect technical solutions, ensuring alignment between business objectives and technical implementation

• Guide technical architecture decisions and help customers build state-of-the-art products & workflows with LLMs via API

• Develop customized pilots, prototypes, and evaluation suites that make the case for customer deployment of our models into customer products and workflows via our API

• Lead hands-on technical workshops and code reviews with customer engineering teams

• Identify common design patterns and contribute insights back to our Product and Engineering teams 

• Maintain strong knowledge of the latest developments in LLM capabilities, implementation patterns, and AI product development stacks

• Travel occasionally to customer sites for workshops, implementation support, and building relationships

• Attend conferences, lead speaking engagements, write blog posts and white papers on topics surrounding the AI space

You may be a good fit if you have

• 4+ years of experience in a technical roles such as Customer Engineer, Forward Deployed Engineer, Software Engineer or Technical Product Manager with a desire to work closely with customers

• Production experience with LLMs including advanced prompt engineering, agent development, evaluation frameworks, and deployment at scale

• Strong programming skills with proficiency in Python and experience building production applications

• Expertise working with common LLM implementation patterns, prompt engineering, evaluation frameworks, agent frameworks, and retrieval frameworks.

• Ability to navigate ambiguity and execute across domains with intellectual openness, finding simple solutions to complex problems

• High cooperation mindset for cross-organizational collaboration, balancing competing priorities with integrity

• Passion for advancing safe, beneficial AI systems through creative technical applications

• Exceptional communication skills to convey technical concepts to diverse stakeholders while maintaining a low ego and collaborative approach

• Fluent in Japanese and English

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

About the role

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.

Responsibilities:

• Partner with account executives across Japan to deeply understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and technical implementation

• Serve as the primary technical advisor to enterprise customers across Japan throughout their Claude adoption journey, from discovery to initial evaluation through deployment. You will need to coordinate internally across multiple teams & stakeholders to drive customer success

• Support customers building with both the Claude API and Claude for Work 

• Create and deliver compelling technical content tailored to different audiences across Japan. You will need to be able to spread the gamut from technical deep dives for engineering & development teams up to business value focused conversations with executives

• Guide technical architecture decisions and help customers across Japan integrate Claude effectively into their existing technology stack

• Help customers develop evaluation frameworks to measure Claude's performance for their specific use cases

• Identify common integration patterns and contribute insights back to our Product and Engineering teams

• Travel occasionally to customer sites for workshops, technical deep dives, and relationship building

• Maintain strong knowledge of the latest developments in LLM capabilities and implementation patterns

You may be a good fit if you have:

• 5+ years of experience in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager

• Native-level Japanese fluency and business-level English required

• Experience working with enterprise customers, navigating complex buying cycles involving multiple stakeholders

• Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more

• Strong technical communication skills with the ability to translate customer requirements between technical and business stakeholders

• Experience designing scalable cloud architectures and integrating with enterprise systems

• Comfortable with python

• Familiarity with common LLM frameworks and tools or a background in machine learning or data science

• Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities

• A love of teaching, mentoring, and helping others succeed

• 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

• 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

About the role

We are seeking a hands-on Security Engineer who thrives in a startup environment.

You'll work alongside product owners and engineers with the objective to secure the products in Startale's ecosystem. Products include a next-generation decentralized exchange with a fully on-chain order book (Strium), a user-facing application (StartaleApp) and a stablecoin (USDSC). This is a hands-on, technical role. You'll be the person who actively tests our systems, hunts for vulnerabilities, models threats against our products, and works with engineers to close the gaps — not the person who writes policies and generates reports. You'll report to the Security Lead and collaborate daily with Backend, Frontend, DevOps, and Blockchain engineering teams.

Why this role

• Startale's products handle user funds and on-chain transactions so security work has tangible impact.
• Owning the security posture of a project at scale and complexity such as Strium is an opportunity for professional growth.
• You will have direct influence over how product security is built across the organization.
• Focus is on driving product security and not on maintaining compliance documentation.
• Our team is backed by and partnering with leading Japanese enterprises so you will have a chance to work in a stable and well-funded company but with the autonomy and speed of a small team.

Key responsibilities

• Security Assessments & Penetration Testing: Conduct hands-on security testing of our applications, APIs, and infrastructure. Simulate real attack scenarios against our products. Find the vulnerabilities before external attackers or whitehat researchers do. Work with engineers to fix issues pragmatically.
• Threat Modeling: Build threat models for new services and features — especially Strium's trading engine, order book, and transaction flows. Identify attack surfaces, model adversary behavior, and define what needs to be hardened before launch.
• Vulnerability Triage & Remediation: Own the end-to-end lifecycle of findings — from discovery through severity assessment, developer-facing write-ups, remediation guidance, and verification of fixes. Coordinate with engineers so issues actually get closed.
• Vulnerability Disclosure & Bug Bounty: Manage incoming whitehat reports, validate findings by reproducing them, assess severity, communicate with researchers.
• AI Tools Security Support: Assess technical risks related to AI tools used within teams (such as data exfiltration, prompt injection, training-on-input), maintain security baselines for AI coding tools and review AI-powered internal tools.

Qualifications

Must-have

• 5+ years of hands-on experience with a focus on application security, penetration testing, or product security.
• Demonstrated ability to find vulnerabilities — through manual testing, architecture and/or code review, or creative attack simulation. You should be able to describe specific bugs you've found and how you found them.
• Practical experience with exchange or trading platform security — from a DEX (preferred) or DeFi protocol. You should understand order book mechanics, transaction flows, wallet security, and the threat landscape specific to trading infrastructure.
• Scripting and automation ability — you write tools and automate to scale security across the stack, not just audit and write reports.
• Experience triaging vulnerabilities and writing clear, actionable remediation guidance for developers.
• Strong written communication in English — you'll write tickets, assessment reports and researcher responses.

Strong plus

• Experience with cloud infrastructure security — least-privilege enforcement, network security, secrets management.
• Experience with container security — network policies, RBAC, pod security standards, image scanning, Dockerfile hardening, base image management.
• Ability to read and review code in at least one of: TypeScript/JavaScript, Solidity, Rust.
• Understanding of software supply chain security, including dependency risks, build integrity, and methods for tracking what components are included in shipped software.
• Experience managing or participating in a bug bounty program (e.g. Immunefi, HackerOne).

Domain plus

• Experience securing AI/LLM tooling in engineering teams — prompt injection risks, data leakage prevention, tool configuration hardening
• Japanese language ability (not required, but useful for company context)

Location / Timezone

• Strong preference for Tokyo-based or Singapore-based candidates - Startale office locations.
• Remote-friendly for exceptional candidates — must have 3+ hours overlap with Tokyo business hours (JST, UTC+9).

Target start date

• As soon as available; realistic target start of Q3 2026.

Target companies

Decentralized exchanges, DeFi protocols, blockchain security firms, L1/L2 chain security teams, or fintech companies with trading infrastructure. We're also open to strong AppSec engineers from cloud-native startups who have genuine interest in web3.

Ideal candidate

You're a hands-on security engineer who finds real vulnerabilities, not just runs scanners. You've secured a trading platform or exchange and understand the threats specific to financial infrastructure — order book manipulation, transaction signing, wallet compromise, front-running. You can take a system, map the attack surface, and come back with findings that matter. You write clear reports that engineers act on, and you know the difference between a theoretical risk and a real one. You're comfortable working independently in a fast-moving team where there's no playbook — you write the playbook.

The Team:
Celonis makes processes work for people, companies, and the planet. As the Celonis Services organization, we are the strategic implementation consulting & transformation arm of a unified Customer Organization aligned to four core mandates:

1. Make Celonis Business Critical: Transform the platform into the central nervous system of our customers’ operations.
2. Scale Customer Health: Drive full platform adoption to ensure long-term value and stability.
3. Focus on High-Value Activities: Prioritize complex, high-impact technical work that moves the needle for Focus & Strategic customers.
4. Empower Career Growth: Foster an environment where every Celonaut owns customer success while accelerating their own professional trajectory.

We deliver production-ready Celonis Platform implementations that drive measurable top, bottom, and green-line impact. Moving beyond “point-in-time” analysis, we utilize a Discover-and-Build approach to solve the world's most complex operational challenges.

In close partnership with Value Engineering, we perform data-driven discovery to validate business hypotheses against real-world data. We then build and deploy operational, AI-enriched solutions on top of the Celonis Platform that automate decisions and optimize workflows at an enterprise scale.

We don't just implement AI for our customers; we live it. Our project delivery lifecycle is accelerated by state-of-the-art AI augmentation, allowing our consultants to focus on high-level, strategic problem-solving. By serving as the "eyes and ears" in the field, we maintain a continuous innovation loop with our Product & Engineering teams, ensuring our frontline learnings directly shape the future of the Celonis Platform.

The Role:
You are an AI Deployment Architect (AIDA). You own the reality of scaling solutions within a customer's actual IT environment and productizing those results. Complementing your colleagues in Applied Value Engineers and Applied AI Engineering, who focus on pre-sales prototyping, you bridge the gap between "the art of the possible" and Business Critical, scaled solutions. As an AIDA, you steer account teams and customers toward AI use cases that are inherently scalable. You are not the primary implementer of these solutions. Instead, you steer the definition of the architectural vision for Consultants to execute and oversee delivery excellence. You remain hands-on for first-of-their-kind production solutions, eventually transitioning to an advisory capacity across a broad "book of work" within your assigned vertical.

The work you’ll do:

• Advise and Safeguard Technical Implementations: Provide architectural oversight for concurrent deployments at Fortune 500 organizations. You act as the final technical authority, maintaining "project-ready" coding skills to troubleshoot and resolve critical production failures that block value realization.
• Architect AI-Enriched Solutions: Collaborate with pre-sales teams to transform experimental prototypes into robust, scalable enterprise applications. You then translate these successful deployments into standardized platform features by maintaining a tight feedback loop with Product and Engineering.
• Engineer Low-Latency Systems: optimize these AI-enriched solutions for high-throughput and minimal latency. You ensure the Celonis Platform handles near-real-time data integration without compromising the user experience of business-critical applications.
• Implement Eval-Ops & Automated Testing: Build rigorous evaluation pipelines to test LLM quality and reliability at scale. You move beyond manual spot-checks by institutionalizing automated benchmarks for model accuracy and safety.
• Deploy LLMOps & Lifecycle Governance: Design systems for continuous model monitoring, cost optimization, and performance tuning. You establish the frameworks for data privacy and compliance within the customer's actual IT environment.
• Troubleshoot Agentic Orchestration: Manage the complexity of multi-agent workflows where agentic activity is triggered by Celonis context and logged back to the platform. You ensure seamless hand-offs between agents and maintain the integrity of the full process loop.
  
  

The qualifications you need:

• More than 4-5 years experience in IT-Consulting, Management Consulting, Process Improvement or a similar area
• Hands-on experience applying AI/ML techniques to solve business challenges is a plus.
• Native Japanese and strong communication in English
• Ability to refactor experimental pilots for production-scale performance and a deep proficiency in Python for building enterprise-grade LLM-based solutions.
• General understanding of companies business processes and related financial metrics and are willing to learn in this area. Knowledge of standard ERPs (SAP and related business processes (Order to cash, procure to pay…) is a plus.
• Enjoy interacting with various customers to understand and interpret business processes
• You are very dedicated and visionary and want to actively drive the Celonis Process Mining technology forward
• Excellent analytical skills, well organised and known for being a quick learner
• Business acumen is a strong plus, supporting the ability to understand client needs, identify value drivers, and deliver strategic, impact-driven recommendations
• Successfully completed your studies in Business Informatics, Computer Science, Information Systems, Economics, Mathematics, or a related field

#LI-DH2

Contractor Details

• Duration: 1 year
• Working location: Japan-based
• Hourly rate: ~6,568 JPY - ~8,490 JPY ($41/hour - $53/hour)
• Expected hours: 30-40 hours/week

Job Overview

Lazarus is seeking an experienced Software Engineer to join our team dedicated to our Japanese market for a 1-year contract. As a contractor, you will be an integral part of our Engineering team, working with clients, senior engineers, and data engineers to facilitate the successful and efficient adoption of our solutions.

Responsibilities

• Work with the engineering and sales teams to gather client requirements and assist in creating implementation plans.
• Assist in configuring and customizing our products to align with client needs and integrate into their existing systems and solutions.
• Participate in the end-to-end implementation process, ensuring timely project completion and client satisfaction.
• Troubleshoot technical issues and collaborate with engineers to provide effective solutions during the implementation phase.
• Document implementation processes, best practices, and solutions for internal knowledge sharing and client reference.
• Work closely with cross-functional teams, including prompt-engineering, sales, support, and development, to ensure efficient and successful customer solution delivery.
• Provide training and technical assistance to clients, guiding them through product functionalities and usage.
• Work with clients and partners to develop optimal prompts for their use cases.
• Continuous learning regarding how LLM’s and associated tools may improve existing and new solutions.

Requirements

• Must be a native Japanese speaker with full working proficiency in reading and writing.
• Basic proficiency in spoken and written English.
• 1-2 years of experience in a technical role, such as technical support, systems administration, software development, or related internships.
• Available for video conferences with customers across North American and Asian time zones, including occasional evening calls as needed.
• Knowledge of programming languages, scripting, and system configurations.
• Familiarity with cloud technologies, APIs, and database management.
• Proven familiarity with LLMs and prompt engineering strategies and tactics.
• Problem-solving skills and a proactive attitude towards learning and troubleshooting.
• Excellent communication skills to effectively interact with clients and internal teams.
• Ability to work collaboratively in a fast-paced environment, adapting to evolving client needs and project requirements.

About Appier 

Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.

About the role

Appier's Playable Ads team (https://www.appier.com/en/blog/what-is-playable-ads)  builds AI-powered playable and video ad experiences that drive dramatically higher engagement and conversion for the world's leading apps and games. We're looking for a Senior Backend Developer with deep expertise in distributed systems and modern backend architecture to design and build the scalable, high-performance services behind these experiences — from creative generation pipelines to the infrastructure that brings our ML models to production. You'll work across microservices, messaging systems, data persistence layers, and system performance optimization, while partnering with ML scientists on MLOps workflows to continuously ship and serve new model versions to end users. You'll also collaborate closely with frontend engineers and product managers to deliver seamless, cross-functional outcomes.

If you're passionate about building backend systems that operate at scale, thrive in cross-functional teams, and want your code to directly power AI-driven ad experiences reaching millions of users, we'd love to talk.

What You'll Work On

• Architect and develop robust, scalable backend services and APIs using ASP.NET Core, owning sizable projects from system design through production operation.
• Design efficient database schemas and optimize data access logic across SQL and NoSQL data stores.
• Implement message-driven communication with high reliability and fault tolerance.
• Partner with ML scientists to build and maintain MLOps pipelines — including model versioning, deployment, serving, and monitoring — ensuring new models are reliably delivered to production.
• Lead system designs, drive technical roadmap decisions, and provide guidance to team members.
• Proactively identify performance bottlenecks, profile critical components, and implement scalable solutions.
• Own and continuously improve system observability, incident management, CI/CD pipelines, and deployment workflows.
• Explore and integrate AI-assisted development tools and emerging technologies to boost team productivity.
• Participate in on-call rotation to ensure product reliability and scalability.

What We're Looking For 

[Minimum qualifications]

• Proficiency in C# and ASP.NET Core, or experience with other object-oriented languages (e.g., Java, Go) with willingness to cross-train in the .NET stack.
• Proven experience in distributed systems, microservice architectures, and designing scalable backend systems.
• Strong expertise in PostgreSQL, MongoDB, or equivalent SQL/NoSQL databases, with hands-on experience in ORM frameworks such as Entity Framework Core.
• Advanced knowledge of message broker systems such as RabbitMQ, Kafka, or NATS.
• In-depth understanding of IO-bound operations, threading, parallelism, and asynchronous programming.
• Practical experience with Docker, container-based deployment workflows, and cloud platforms (AWS, GCP, or Azure).
• Hands-on experience with CI/CD pipelines, observability tooling, and production operational practices.
• Demonstrated ability to write clean, well-documented code and solve complex problems analytically.
• Clear communicator who can explain technical decisions to both technical and non-technical stakeholders and enjoys working in a fast-paced, collaborative environment.
• Proficient in using LLM-powered development tools (e.g., GitHub Copilot, Cursor, ChatGPT) to accelerate productivity.

[Preferred qualifications]

• BS/MS degree in Computer Science or a related field.
• Experience with MLOps practices such as model serving infrastructure, A/B testing frameworks, or ML pipeline orchestration tools.
• Leadership experience such as mentoring junior engineers, leading code reviews, or facilitating agile processes.
• Experience with performance profiling and debugging tools, high-performance network services, or FFI integrations for performance-critical components.
• Solution-oriented mindset with a focus on system sustainability, and willingness to explore emerging technologies into backend systems.

[Language]

Fluent in English, Japanese language proficiency is not required.

Open to overseas candidates/Visa Support
This position can be based in Tokyo, Japan or Taipei, Taiwan. For international candidates, Appier's Japan office provides visa sponsorship to ensure a smooth relocation transition to Japan.

#LI-AK1

About Appier 

Appier (TSE: 4180) is an AI-native Agentic AI as a Service (AaaS) company that empowers businesses to create value through cutting-edge AdTech and MarTech solutions. Founded in 2012 with the vision of “Making AI Easy by Making Software Intelligent,” Appier helps businesses turn AI into ROI through its Ad Cloud, Personalization Cloud, and Data Cloud—each powered by Agentic AI that enables autonomous, adaptive, and real-time decision-making. Today, Appier operates 17 offices across APAC, the US, and EMEA, and is listed on the Tokyo Stock Exchange. Learn more at www.appier.com.

About the role

AI is reshaping how brands connect with consumers — and at Appier, we’re at the forefront. Our Playable Ads team builds AI-powered ad experiences — from interactive playable formats to video ads — that drive dramatically higher engagement and conversion for the world’s leading apps and games. We’re looking for a Senior Machine Learning Scientist to push the boundaries of what’s possible — applying cutting-edge ML, generative AI, and optimization techniques to create smarter, more compelling ad creatives at scale.

If you’re excited about turning the latest advances in AI into products that reach millions of users, and you thrive at the intersection of research and real-world impact, we’d love to talk.

What You’ll Work On

• Apply ML and generative AI techniques to problems such as creative optimization, user behavior prediction, engagement modeling, and dynamic content generation for various creative formats.
• Own the end-to-end ML lifecycle — from problem framing and experimentation through to production deployment and continuous improvement.
• Collaborate closely with product, engineering, and design teams to translate business goals into well-defined ML solutions.
• Conduct offline and online evaluation, A/B testing, and performance monitoring to continuously improve model quality and business impact.
• Stay current with the latest research in areas like LLMs, multimodal models, reinforcement learning, and recommendation systems, and proactively propose innovative applications to the team.
• Mentor fellow scientists and contribute to the team’s technical standards and culture.

What We’re Looking For

[Minimum qualifications]

• Master’s or Ph.D. in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or a related field.
• Solid understanding of modern ML models and algorithms, with hands-on experience in at least one area such as prediction/optimization, generative models, recommendation systems, computer vision, or reinforcement learning.
• Proficient in Python and ML frameworks such as PyTorch or TensorFlow.
• Practical experience taking ML models from prototype to production, including pipeline development and performance monitoring.
• Strong analytical and problem-solving skills with the ability to diagnose model behavior and improve training pipelines.
• Clear communicator who can explain technical ideas to both technical and non-technical stakeholders and enjoys working in a fast-paced, collaborative environment.
• Proficient in using LLM-powered development tools (e.g., GitHub Copilot, Cursor, ChatGPT) to accelerate productivity.
• Ability to balance cutting-edge research with time-to-market constraints, delivering iterative PoCs that validate product hypotheses and translate into production-ready solutions.

[Preferred qualifications]

• Publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, KDD, RecSys).
• Experience in the advertising technology or MarTech domain.
• Contributions to open-source projects or active involvement in research communities.

#LI-AK1

At AKQA (part of WPP) we believe in the imaginative application of art and science to create beautiful  ideas, products and services. We exist to create the future together with our clients. 

The Technology Director is responsible for leading and growing the Tokyo technology team and client portfolio. Working alongside the local leadership team and regional Chief Technology Officer, you will own the Tokyo technology strategy, plan how to grow and service the Tokyo studio engagements and foster a high-performing technology team, while ensuring successful commercial engagements and technical program delivery.

You will build and lead a team of experts and coordinate with regional practice leaders and partners to deliver technology outcomes for the Tokyo client portfolio. As a member of the regional AKQA Technology Executive, you will also contribute to regional technology initiatives and practice development.

By deeply understanding client business challenges, experience goals, and technical requirements, the Technology Director serves as the central decision-maker ensuring world-class digital experiences powered by modern web architectures and frameworks, MarTech, and AI technologies.

This role reports to the local Delivery Director and the APAC CTO.  Primary reports for this role include Solution Architects, Technical Leads, and Principal Engineers.

Key Responsibilities

Technical Delivery Leadership

• Lead the technical setup and onboarding for web and digital product development projects.
• Own architecture reviews, code reviews, and technical risk assessments.
• Establish quality, performance, and security standards to ensure high-quality delivery.
• Lead high-complexity projects independently within client engagements.
• Drive technical decision-making and propose optimal implementation approaches.
• Be hands-on in delivering technology engagements and solutions as required, while building the Tokyo technology practice.

Proposal & Pre-Sales Support

• Lead RFP/RFI analysis, technical approach design, and proposal development.
• Own technical presentations, client communication, and estimation.
• Contribute to business growth by designing competitive, technology-driven solutions.
• Lead and coordinate bringing in regional technology colleagues and partners in order to create compelling RFP responses highlighting the best of AKQA’s capabilities
  
  

Team Management & Capability Building

• Lead and mentor architects, Technical Delivery Managers, and other technology team members.
• Define and maintain technical standards, development processes, and best practices to improve productivity and quality.
• Support hiring, talent development, performance management, and community engagement to strengthen the technology discipline.
• Ensure the team structure is maintained, and appropriately sized for the current and pipeline client engagements.
• Guide decisions on the mix of resources across the studio, including the mix of permanent and contract roles, and decisions on when to utilise partners within the AKQA and Itochu networks.
• Work with regional practice leaders to develop practice related talent

Solution Development & Innovation

• Continuously evaluate emerging technologies such as AI/LLM, MarTech tools, cloud platforms, and modern web frameworks.
• Provide technical insights that drive client proposals and product improvements.
• Collaborate with global teams to adopt and localize best practices and global capabilities.

Stakeholder Communication

• Lead technical discussions with client executives, IT leaders, and product owners.
• Promote collaboration with AKQA's regional and global team, and partnerships with partners.
• Work closely with PMs, designers, and strategists to ensure alignment across all project disciplines.

Reputation

• Involvement in AKQA's marketing and PR - focused on both potential clients and potential employees.
• Drive initiatives to connect with and attract key talent to AKQA.
• Foster and contribute to industry thought leadership.

QUALIFICATIONS & CHARACTERISTICS 

• Strong interest and ongoing learning in AI, LLMs, generative AI, MarTech, and emerging technologies
• Experience designing architecture for large-scale digital products
• Experience working within a global or distributed organization
• Public technical contributions such as conference speaking, publishing, or OSS involvement
• knowledge of modern web architecture, APIs, cloud platforms (GCP, AWS, Azure / Vercel, Netlify), and software engineering best practices

About Appier 

Appier is an AI-native Agentic AI as a Service (AaaS) company that uses artificial intelligence (AI) to power business decision-making. Founded in 2012 with a vision of democratizing AI, Appier’s mission is turning AI into ROI by making software intelligent. Appier now has 17 offices across APAC, Europe and U.S., and is listed on the Tokyo Stock Exchange (Ticker number: 4180). Visit www.appier.com for more information.

About The Role

We’re building agentic and recommendation products that power next-gen digital marketing. You will lead an engineering team at the intersection of ML systems, LLM/agent orchestration, and enterprise SaaS to deliver reliable, measurable outcomes for marketers—faster execution, smarter budget allocation, and differentiated brand performance.

Our goal is to build Marketing Agents (e.g., Audience Agent, Campaign Agent and Insight Agent) and Consumer-Facing Agents (e.g., Service Agent, Sales Agent), underpinned by a One Data Platform that enables trustworthy personalization and decisioning at scale.

What You'll build

Agentic Marketing Automation

• Natural language task assignment: users describe objectives and constraints in plain language; agents plan, execute, and report.
• Amplifying brand advantage: systems that help strong brands compound performance while giving others actionable levers to close gaps.
• One Data Platform integration: unify identity, events, product catalog, and campaign data to drive consistent decisions across products.

[Product Areas]

• Marketing Agents
  • Audience Agent: segmentation, targeting strategies, cohort insights, next-best audience.
  • Campaign Agent: multi-step campaign planning, creative/testing suggestions, launch & iteration, performance diagnosis.
• Consumer-Facing Agents
  • Service Agent: post-purchase journeys, retention, support deflection, cross-sell triggers.
  • Sales Agent: lead qualification, outreach recommendations, pipeline nudges (where applicable).
• Recommendation products: ranking, next-best-action, uplift modeling, personalized content/channel selection.

Responsibilities 

Engineering leadership

• Lead a team of engineers (and partner closely with ML scientists) to deliver enterprise-grade agent and recommendation capabilities.
• Translate product goals into technical strategy, milestones, and execution plans; drive delivery with high quality and predictable cadence. 
• Establish engineering excellence: code quality, testing, observability, incident response, and continuous improvement.
• Build an environment of humble, hungry, smart execution—measure outcomes, iterate quickly, reduce waste.

Agentic Systems & ML Product Delivery

• Design and ship agent frameworks: planning/execution loops, tool calling, memory, retrieval, safety guardrails, and evaluation.
• Define evaluation methodology for agents: offline benchmarks, online experiments, success metrics, and human-in-the-loop review flows.
• Assure solid integration with One Data Platform: data contracts, feature availability, privacy controls, and reliability SLAs.
• Partner with Product, Design, Data/ML, and GTM to ensure model behavior aligns with user needs and business goals.

Stakeholder & Culture

• Drive stakeholder alignment: connect engineering objectives to business outcomes (revenue, retention, customer value).
• Promote an autonomous culture: empower autonomous decision-making for both the team and the systems you build.
• Manage fast-paced experimentation while ensuring security, compliance, and enterprise readiness.

About you 

[Minimum qualifications]

• 8+ years professional experience as a Software Engineer; 4+ years in a management/leadership role.
• Strong communication in English (written and verbal).
• Degree in Computer Science / Informatics or equivalent practical experience.
• Proven track record delivering enterprise-grade products (reliability, security, observability, performance).
• Experience working with or managing engineers and ML scientists.
• Experience delivering solutions using Agile principles.

[Preferred qualifications]

• Experience building LLM/agentic systems in production (tool use, RAG, orchestration, evaluation).
• Hands-on background with ML systems (recommendation, ranking, attribution, uplift, LTV, forecasting) and their productionization.
• Familiarity with data platforms (event pipelines, identity resolution, feature stores, lakehouse/warehouse) and data governance.
• Experience with A/B testing and causal measurement; comfortable making tradeoffs using metrics.
• Exposure to MA/CRM domains: segmentation, journeys, omnichannel messaging, campaign ops, budget pacing.
• Experience in leading hybrid (onsite/remote) engineering team.

About Us (Appier Engineering)
At Appier Engineering, we aim to be humble, hungry and smart. We improve through constant measurement and feedback—building less and talking more to ensure outcomes users love while reducing waste. We innovate by failing well, adapt quickly, and stay efficient and responsive when needed. We’re looking for an Engineering Manager who embodies these values through work and life experiences.

About the role 

We are seeking an experienced Machine Learning Lead to helm our Machine Learning team. 

In this pivotal role, you will be the engineering architect behind Vulcan’s core AI capabilities. You will act as the nexus between Research, Platform, and Product. Your mission is to translate cutting-edge findings on GenAI threats into robust, production-ready machine learning models that power our GenAI Security Guardrails (Blue Team) and Automated Vulnerability Assessment (Red Team). 

Crucially, you will serve as the bridge between deep tech and business strategy, articulating technical constraints (like FLOPS and latency) to leadership and clients while guiding the engineering direction. 

Key Responsibilities

1. Model Development & Optimization (Training & Fine-tuning):

• Research to Production: Collaborate with the Security Research Team to operationalize new threat detection techniques. They identify the "what" (e.g., new prompt injection patterns); you determine the "how" (model architecture, training strategy). 
• Fine-tuning & Adaptation: Lead the fine-tuning of Language Models (e.g., using LoRA/PEFT) to optimize for our supported muti-lingual languages and specific security intents.
• Multimodal Readiness: Prepare the system for Multimodal (Text + Image/Audio) capabilities. Evaluate and implement models to detect visual prompt injections and non-textual threats as the product evolves. 

2. MLOps& Data Infrastructure: 

• Enhance & Scale MLOps: Take ownership of our existing ML pipelines. Focus on optimizing and scaling CI/CD/CT workflows to improve training efficiency and deployment velocity. 
• Data Governance: Implement and enforce rigorous Data Versioning strategies (e.g., DVC) to ensure complete reproducibility of model artifacts and datasets.
• Monitoring & Reliability: Maintain rigorous monitoring for model drift and performance, ensuring high reliability in a production security environment.

3. Cross-Functional Implementation & Leadership:

• Platform Collaboration: Work closely with the Platform Engineering Team to integrate ML models into the broader product architecture. Ensure seamless interaction between model inference services and the main platform logic. 
• Team Leadership: Lead and mentor Machine Learning Engineers, fostering a culture of engineering rigor, code quality, and operational excellence.
• Resource Management: Manage GPU resources and compute budgets effectively for both training and inference workloads. 

4. Technical Strategy & Stakeholder Management:

• Translating Tech to Business: Act as the technical voice of the ML team. You must effectively explain complex ML concepts (e.g., FLOPS, quantization trade-offs, model latency vs. accuracy) to executive leadership and clients. 
• Cost-Benefit Analysis: Justify compute resource investments. Articulate the trade-off between infrastructure costs (GPU hours) and performance gains to non-technical stakeholders. 

Qualifications

• Experience: 5+ years in Machine Learning Engineering, with specific experience in leading technical projects or mentoring engineers.
• Communication & Business Acumen: Exceptional ability to distill complex technical topics (e.g., compute complexity, infrastructure costs) into clear, business-relevant insights for decision-makers.
• MLOps Proficiency: Proven experience in optimizing ML pipelines and infrastructure. Familiarity with tools like MLflow, Kubeflow, Airflow, and Data Versioning tools (DVC, etc.).
• Engineering First: Proficient in Python, Docker, and Kubernetes. You treat ML models as software artifacts that need testing and version control.
• NLP & LLM Expertise: Experience with Transformer architectures, Embeddings, and LLM fine-tuning. Familiarity with frameworks like PyTorch, Hugging Face, and vLLM.
• Language Support: Experience processing or fine-tuning models for multi-lingual environments. 

Nice to Have

• Multimodal Expertise: Experience working with Multimodal models (Image-to-Text, Text-to-Image, VLMs like CLIP, LLaVA).
• Security Awareness: Understanding of GenAI security threats (e.g., Prompt Injection).
• High-Performance Computing: Experience optimizing inference speed (quantization, distillation, vLLM) for real-time applications.
• Vector Database: Experience with Vector DBs for RAG applications. 

Why Join Us? 

• Innovative Environment: Be part of a company at the forefront of technology to provide security in GenAI, with opportunities to work on groundbreaking projects. 
• Growth Opportunities: Take your career to new heights with our career development programs and growth-focused culture. 
• Dynamic Team: Join a multi-cultural and dynamic team of dedicated professionals who inspire and support each other. 
• Compensation: Competitive salary and benefits package, commensurate with experience and performance. 

Application Process 

• If you're ready to embark on this exciting journey and contribute to shaping the future of GenAI security, please submit your resume outlining your relevant experience and motivation for applying.
• If you prefer a direct connection or have specific questions about our vision, feel free to reach out to our Co-founder, Alvin Kwock, via LinkedIn. 

About Us

AIFT is at the forefront of AI safety and security, developing cutting-edge solutions, Vulcan Attack (automated vulnerability assessment/red teaming) and Vulcan Protect (real-time monitoring), to ensure AI systems are robust, trustworthy, and aligned with societal needs.

Our Product

Vulcan is a cybersecurity solution specifically designed for GenAI, offering two core services: Red Team (vulnerability assessment) and Blue Team (real-time defense). It ensures GenAI compliance, cybersecurity robustness, and operational integrity. 

Since its official launch in 2024, Vulcan has been recognized by the international standard-setting organization OWASP as a certified vendor for LLM & GenAI security testing and assessment. It is one of the few solutions capable of supporting multiple Asian languages (Traditional Chinese, Simplified Chinese, Japanese, Korean, Thai) and Standard Arabic. 

The Role

We are seeking a passionate and highly skilled GenAI Security Researcher to join our team. You will conduct applied and theoretical research into AI vulnerabilities, attack/defense methods, and security/safety benchmarking. Your work will directly shape our AI safety products, contribute to research communities, and influence industry standards and regulations.

What You'll Do

• Research: Investigate adversarial attacks, data poisoning, prompt injection, jailbreaks, and other AI system vulnerabilities in multi-modalities (e.g., text, image, video, and audio). Design and evaluate mitigation strategies, including fine-tuning, guardrails, content filtering, and robust model architectures.
• Benchmarking: Develop and maintain AI security evaluation frameworks, datasets, and performance metrics.
• Collaboration: Partner with product and partnership teams to integrate the findings into our AI security solutions.
• Dissemination: Publish findings in top-tier conferences and journals, present at industry events, and contribute to open-source initiatives.

What We're Looking For

• Research skills: Advanced degree (e.g., MSc/PhD) with strong analytical thinking, problem-solving skills, and ability to translate research into practical solutions.
• Knowledge: Deep understanding of relevant techniques, such as generative AI, security & privacy, computer vision, signal processing, and human-computer interaction.
• Communication skills: Clearly explain complex concepts in layman's terms.
• Proficiency in English: Write and read documents, communicate with team members in English.
• Teamwork: Work closely with our members to deliver value.
• Agility: Adapt quickly to changing research priorities and emerging AI security threats.
• Coding skills: Proficiency in Python and experience with experimentation.

Nice to Have

• Publication record in top-tier journals and conferences in AI, security & privacy, computer vision, signal processing, and human-computer interaction.
• Experience with white-hat hacking and security tools.
• Familiarity with industry frameworks, such as OWASP Top 10 LLM, MITRE ATT&CK, and security standards.
• Proficiency in multiple languages.

Why Join Us

• Solve high-impact AI security challenges shaping the future of trustworthy AI.
• Collaborate with world-class researchers and engineers in a mission-driven environment.
• Competitive compensation, flexible working arrangements, and professional growth opportunities.

How to Apply

• Submit your English CV containing education and work experience with a publication list (underline your name in the author list).