Forward Deployed Engineer

As a Forward Deployed Engineer at DevRev, you will work closely with our pre- and post-sales Customer Experience team by developing solutions over the core platform via applications written in TypeScript, JavaScript, Python, etc. One of the key functions of this role is, building the Knowledge Graph that includes integration of DevRev with other SaaS and non-SaaS systems through webhooks and APIs and/ or real-time communication architectures. You will be expected to employ your creativity and expertise to ideate and shape how AI, analytics and workflows are used in customers' processes. 

What You’ll Do

• Customer-facing: 30% working directly with customers 

Coding & Integration: 70-80% hands-on technical implementation

• Build & Deploy Solutions: Design, develop, and launch AI agents, integrations, and automations that connect DevRev with customers' existing tech stacks and workflows.
• Integrate Systems: Connect DevRev with SaaS and non-SaaS platforms through APIs, webhooks, and real-time communication architectures for seamless data flow.
• Optimize AI Performance: Apply prompt engineering, fine-tune semantic search engines, and leverage generative AI techniques to enhance agent accuracy and user experience.
• Own Data Insights: Write SQL queries, perform data analysis, and build dashboards to surface insights that drive customer decision-making.
• Prototype & Iterate: Develop rapid proofs-of-concept, conduct live technical demos, and refine solutions based on customer and stakeholder feedback.
• Lead Cross-functional Collaboration: Maintain constant communication loops with customers, engineering, product, customer success, support, and revenue teams to ensure alignment.
• Guide Technical Adoption: Learn and master new tools, then guide customers through critical workflows like code repository integrations and advanced configurations.
• Travel Ready: Willingness to travel up to 30% for on-site implementations, technical workshops, and customer engagements.

What You Bring

• Experience: 5+ years in software development, systems integration, or platform engineering. Customer-facing experience is a plus.
• Coding Skills: Strong proficiency in TypeScript, JavaScript, Python, data structures and algorithms. (Nice to have: Go)
• Design & Deploy AI Agents: Build and configure intelligent solutions leveraging snap-ins, connectors (AirSync), workflows, and AI agents on the DevRev platform to solve real customer problems.
• Applied AI Knowledge: Familiarity with large language models (LLMs), prompt engineering, frameworks like RAG and function calling, and building evals to validate agentic AI solutions.
• Integration: Deep experience with large-scale data synchronization (one-way and two-way), API integration patterns (REST, GraphQL, webhooks), and event-driven/pub/sub architectures.
• Cloud & Deployment: Hands-on experience deploying on serverless and edge platforms (AWS Lambda, Google Cloud Functions) with modern DevOps practices (CI/CD, containers, observability).
• Data Transformation: Skilled in data mapping, schema alignment, and working with heterogeneous systems. Understanding of data modeling and graph data structures.
• Observability: Experience implementing clear logging, actionable error surfacing, and telemetry to support faster debugging and issue resolution.
• Context-Aware Systems: Familiarity with Model Context Programming (MCP) for building adaptive, context-aware integrations.

Communication and Customer Empathy: Strong written and verbal skills

• Background: Bachelor's or Master’s degree in Computer Science, Engineering, or related discipline. Advanced degrees or certifications in AI/architecture frameworks (e.g., TOGAF, SAFe) are a plus

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

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.

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 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.