Project Overview

This is a cutting-edge initiative to integrate Large Language Models (LLMs) with WorldQuant's proprietary strategy management tools. The project aims to provide AI-assisted insights, automate routine analytical tasks, and enable natural language interactions for Portfolio Managers to more efficiently analyze, maintain, and enhance their trading strategies. This involves building foundational infrastructure, developing robust data pipelines for metrics and features, and creating a secure, user-centric interface with a strong focus on protecting intellectual property.

The Role:

We are seeking a talented and motivated Full-Time Software Engineer to play a key role in the development and enhancement of this AI-driven platform. You will be responsible for designing, building, and maintaining critical components of the system, primarily focusing on the Model Context Protocol (MCP) servers that form the backbone of the platform. This includes enhancing existing MCPs, such as our proprietary command-line interface for strategy data, developing new MCPs for internal data system integration, strategy analysis, and performance metrics, and contributing to the secure and effective use of LLMs.

Key Responsibilities

• Design, develop, test, and deploy robust and scalable MCP servers and related tools in Python.
• Enhance existing MCPs, including our internal data access tools, to ensure reliable access to strategy metadata, historical PnL data, and PnL attribution by risk factors.
• Develop new MCPs, including but not limited to MCPs for direct data system integration, MCPs for strategy analytics, and MCPs for performance reporting.
• Design and implement secure prompt engineering techniques to interact with LLMs, ensuring effective information retrieval while minimizing the risk of intellectual property leakage.
• Collaborate with project managers, technical leads, and other developers to define technical specifications and integrate various data sources.
• Work on API development and integration, ensuring seamless data flow between different systems (internal knowledge management systems, simulation systems, data warehouses).
• Implement data parsing and manipulation logic for various formats (JSON, CSV).
• Contribute to the design and implementation of data pipelines for strategy metrics and features.
• Address and resolve bugs and issues in existing MCP tools and infrastructure.
• Participate in code reviews, and contribute to unit and integration testing efforts.
• Create and maintain technical documentation for developed components.
• Stay updated with emerging technologies and methodologies in AI, LLMs, prompt engineering, and financial technology.

What You’ll Bring:

Core Skills:

• Strong proficiency in Python programming.
• Proven experience in API development, integration, and consumption.
• Solid understanding of database interaction, data access patterns, and data modeling.
• Experience with data parsing and manipulation libraries and techniques (e.g., pandas, JSON, CSV).
• Understanding of or experience with prompt engineering principles for Large Language Models
• Awareness of data security and intellectual property protection considerations in the context of AI and LLM applications

Domain-Specific Knowledge (Highly Beneficial):

• Familiarity with financial data (e.g., PnL, Sharpe ratio, alpha, risk factors, AUM).
• Experience with quantitative trading systems, market data systems, or strategy management platforms (familiarity with internal data systems or command-line data tools is a significant plus).

Technical Environment Familiarity (Helpful):

• Experience working in a Linux environment.
• Understanding of Command Line Interface (CLI) tools and development.
• Familiarity with version control systems (e.g., Git).

Soft Skills

• Excellent problem-solving and analytical skills.
• Strong collaboration and communication skills, with the ability to work effectively in a team.
• High attention to detail and commitment to delivering high-quality software.
• Ability to learn quickly and adapt to new technologies and complex systems.

Education

• Bachelor's or Master's degree in Computer Science, Engineering

Role Purpose

As a Senior Backend Software Engineer (Fixed Term Contract) within Boku’s Engineering organisation, you will be one of a small group of engineers delivering new products as part of Boku’s Innovation department. A new suite of products being built from the ground up. This is a greenfield development engagement: the work is scoped to designing and building new software, not maintaining or extending existing production services. You will work in a small, high-autonomy team with a clear remit and a defined delivery horizon, reporting to the Head of Product and Engineering.

Key Responsibilities

Backend Engineering

• Design and build production-grade services using Java and Spring Boot, targeting high throughput, low latency, and high availability (99.99%+).
• Implement and evolve RESTful/gRPC/MCP and event-driven APIs supporting payment initiation, callback handling, reconciliation, and settlement flows.
• Build for fault tolerance and resilience: circuit breakers, retry logic, idempotency, and graceful degradation under load. Maximum observability and telemetry at the core of the build to ensure easy support.
• Optimise service performance through profiling, load testing, and careful data access layer design (SQL and NoSQL).
• Collaborating with colleagues and off-shore development teams providing code-reviews and guidance as necessary to team members and development studios.

Payment Systems

• Build the core components of Payout, Card Processing and FX systems from scratch, including a payout processing engine, AI agent treasury orchestration layer, and cash forecasting service. This work is entirely new development and there is no existing codebase to maintain or inherit.
• Contribute to PCI DSS compliant system design and implementation, including sensitive data handling, audit logging, and access control.

Frontend Contribution

• Contribute React-based frontend components for internal tooling, operational dashboards, and merchant-facing interfaces where required.
• Work with Product and Design to deliver functional, well-tested UI features that meet Boku's quality bar.

FX & Treasury Integration (Desirable)

• Support integration with FX data sources including Bloomberg feeds, for use in real-time rate pricing, settlement FX, and treasury risk tooling.
• Contribute to cash position and FX exposure monitoring services, working alongside Finance and Treasury stakeholders.

Reliability & Operations

• Instrument projects with observability from day one: structured logging, distributed tracing, metrics, and alerting built as part of the product, not retrofitted. On-call and incident management for existing Boku production services are outside the scope of this contract.
• Instrument services with structured logging, distributed tracing, and metrics; contribute to SLO/SLA definitions and alerting.
• Set up CI/CD pipelines, container build configuration (Docker/EKS), and code quality gating (SonarCloud, SAST) as new infrastructure built to Boku’s engineering standards and handed over as part of the finished product.

Key Skills, Experience and Competencies

Required

• 5+ years of backend engineering experience, with deep expertise in Java and the Spring Boot ecosystem (Spring MVC, Spring Data, Spring Security).
• Demonstrable experience building and operating high-throughput, high-availability distributed payment or financial services systems.
• Strong understanding of payment system architecture: idempotency, exactly-once delivery, reconciliation, and settlement flows.
• Experience with relational databases (PostgreSQL, MySQL) and messaging systems (Kafka, RabbitMQ, or equivalent).
• Familiarity with container-based deployment (Docker, Kubernetes/EKS) and CI/CD pipeline tooling (GitHub Actions or equivalent).
• Experience with PCI DSS compliant system design and secure coding practices.
• Strong communication skills; ability to work effectively with Product, Architecture, and Operations in a globally distributed team.

Preferred

• React frontend development experience sufficient to contribute to internal tooling and dashboards.
• Experience integrating with Bloomberg data feeds (BFIX, B-PIPE, or similar) or other real-time FX data sources.
• Background in FX processing, treasury systems, or multi-currency settlement.
• Experience with financial messaging standards (ISO 20022, SWIFT MT/camt formats).
• Prior work in a payments processor, PSP, or fintech operating across multiple markets.

AI & Agentic Systems

• Practical experience building or integrating LLM-powered features into production services, including prompt engineering, tool/function calling, and structured output handling via APIs such as Anthropic or OpenAI. Familiarity with AWS Bedrock is ideal.
• Experience designing or contributing to agentic workflows: multi-step autonomous processes where models plan, call tools, and act on results — including handling retries, failure modes, and human-in-the-loop checkpoints.
• Familiarity with MCP (Model Context Protocol) or similar tool-use frameworks for connecting AI models to internal APIs, databases, and external services.
• Comfortable using AI-assisted development tooling (e.g. Claude Code, GitHub Copilot, Cursor) as part of day-to-day engineering workflow, and able to reason critically about where AI assistance adds value versus where it requires human judgement.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
• 5+ years of professional software engineering experience in backend-heavy roles.
• Prior experience in a regulated financial services or payment processing environment strongly preferred.

Why Join Boku?

Impact: Work on payment infrastructure that processes billions of dollars annually, serving some of the world's largest digital commerce platforms across 65 countries.

Focus: A fixed term engagement with a clearly scoped remit, embedded within a high-calibre engineering team operating on greenfield and core platform work.

Culture: A collaborative, inclusive engineering culture that values craft, rigorous thinking, and delivery. Boku is a genuinely global company with deep expertise in local payment markets.

Benefits: Competitive day rate, flexible working arrangements, and Singapore-based team with global stakeholder exposure.

We’re a fast-growing cloud-native digital bank looking for a Lead SRE / Platform Engineer to drive initiatives to improve the reliability, resilience, and efficiency of the platform that powers our products. This is a hands-on role with leadership responsibilities: you’ll help set the technical direction for how we operate, scale, and secure our infrastructure, and you’ll build the systems that let us move quickly without breaking things.
You’ll be part of a core team that is trusted to keep it running smoothly, make it faster, and turn toil into code.

What you’ll do

• Own the observability platform. Logs, metrics, traces, events — the full picture. Make signals actionable, reduce alert fatigue, and give every team the tools to understand their systems in production.
• Build agentic SRE systems. Design and ship AI agents that investigate incidents, execute runbooks, automate remediation, and close the loop on production issues. Bring context and harness engineering discipline to agent design: grounded context, well-scoped tools, evals, and guardrails.
• Automate the platform. Turn manual processes into self-service. Every recurring operational task is a candidate for elimination.
• Drive resiliency automation. Lead initiatives such as chaos engineering, cost and performance optimization, and capacity forecasting.
• Lead through influence. Set technical direction, mentor engineers, help unblock them when they hit issues, and write the design docs that get referenced for years. Raise the bar on what “operational excellence” means here.
• Be the calm in the storm. Jump in to diagnose and remediate critical infrastructure issues. Support the team during critical deployments — you're expected to be hands-on when it matters most.

What we’re looking for

• 8+ years in SRE, platform, or infrastructure engineering, with deep production ownership of a non-trivial cloud platform.
• Strong system design chops. You can reason end-to-end about distributed systems and event-driven architectures, including failure modes and the tradeoffs between consistency, availability, latency, and cost.
• AWS and Kubernetes experience. Comfortable with EKS internals, networking, IAM/IRSA, service mesh (Istio), and the control-plane/data-plane split.
• Hands-on with the rest of our stack — Kafka, Aurora PostgreSQL / RDS PostgreSQL, S3, ELB — or equivalent managed data and networking primitives.
• Proven track record owning resiliency in a high-velocity environment: incident command, postmortems that actually change things, SLO-driven engineering, progressive delivery.
• Experience with context engineering and harness engineering — building LLM and agent systems where the prompt, retrieved context, tool surface, and eval harness are first-class engineering artifacts.
• A clear vision for what zero-downtime, zero-touch, zero-trust looks like in practice, and a track record of moving real systems toward it.
• Fluent in IaC (Terraform, Helm, or similar) and CI/CD. You believe platforms are products and treat them as such.
• FinOps mindset. Comfortable analyzing cloud cost reports, identifying inefficiencies, and driving optimization initiatives that balance cost with performance and reliability.

Our ideal candidate has

• Financial services or other regulated-environment experience.
• Experience integrating AI/LLM systems into production operational workflows — not just experiments.
• Expertise in OpenTelemetry and the broader observability ecosystem.
• Experience with Sumologic and PagerDuty (or equivalent observability and incident management tooling).
• A continuous learning mindset — you stay current and bring new ideas to the table.
• Strong stakeholder communication and management skills — you can translate technical concepts for non-technical audiences and build alignment across teams.

We’re not hiring someone to run models. We’re hiring someone who builds systems that think.

At SimplifyNext, our AI Engineers are core to how we deliver transformation — designing and deploying intelligent systems that genuinely change how organisations operate. You won’t be a supporting act to another team. You’ll be the one building the agents, pipelines, and infrastructure that make our AI products real.

We work across public sector and enterprise, at the intersection of AI, automation, and product-led transformation. If you’re energised by hard engineering problems, care about production outcomes - not just research benchmarks - and want your work to reach real users at scale, read on.

What You'll Do

1. Build Agentic AI Systems

• Design and build sophisticated AI agents capable of independent operation, complex decision-making, and self-correction across domain-specific contexts.
• Develop orchestration workflows using frameworks such as LangChain, LangGraph, and/or the Microsoft Bot Framework to create robust conversational and task-oriented agents.
• Implement Retrieval-Augmented Generation (RAG) systems that connect agents to live, accurate knowledge bases — reducing hallucinations and improving output quality.
• Build Memory, Reasoning, and Planning (MRP) capabilities so agents can maintain context, reason across information, and execute multi-step plans.
• Design Agent-to-Agent (A2A) communication protocols that allow multiple autonomous agents to collaborate, delegate tasks, and exchange information securely.
• Work with LLM serving solutions (Ollama, vLLM) to ensure efficient, scalable inference in production environments.

2. Deploy and Operate at Scale

• Deploy and manage AI systems on major cloud platforms — AWS, Azure, or GCP — ensuring high availability, security, and scalability.
• Containerise applications with Docker and orchestrate deployments with Kubernetes, including end-to-end on-premise cluster setup and management.
• Build and maintain CI/CD pipelines using tools like Argo (Argo Workflows, Argo CD) for reliable, automated delivery of AI services.
• Expose AI capabilities through well-documented, performant APIs that integrate seamlessly with client-facing systems and applications.

3. Train and Fine-tune Models

• Train, fine-tune, and optimise custom AI models using TensorFlow and/or PyTorch, particularly where off-the-shelf models don’t meet specific project requirements.
• Run structured experiments — hyperparameter tuning, ablations, model evaluation — to hit performance targets with confidence.
• Stay current with the latest developments in large language models and agentic AI, and bring new techniques into our systems proactively.
• Work across diverse data modalities: text, image, time-series, and graph-structured data.

Who You Are

Must-Have

• Production mindset — you’ve shipped AI systems to real users, not just demos.
• Strong fundamentals in agentic AI — you understand how to design agents that are reliable, not just impressive.
• Hands-on with at least one major cloud platform (AWS, Azure, or GCP) for deploying and managing AI workloads.
• Solid Python engineering skills and comfort working in a Git-based, collaborative codebase.
• Experience with containerisation (Docker) and orchestration (Kubernetes) in real deployment contexts.
• Clear communicator — able to explain complex technical decisions to non-technical stakeholders.

Good to Have

• 3–7 years in AI/ML engineering or a closely related role (data engineering, MLOps, applied research).
• Hands-on experience with LangChain, LangGraph, Ollama, vLLM, or similar orchestration and serving tools.
• Demonstrable RAG system implementation and optimisation experience.
• Familiarity with Memory, Reasoning, and Planning (MRP) concepts and Agent-to-Agent (A2A) protocol design.
• Experience with MLOps tooling, particularly Argo Workflows and Argo CD.
• Proficiency in TensorFlow and/or PyTorch for model training and fine-tuning.
• Exposure to knowledge graphs, semantic web technologies, or prompt engineering strategies.

This role is not for you if…

• You’ve only worked with AI in sandboxed or prototype environments and haven’t dealt with production reliability challenges.
• You prefer to work from a detailed spec rather than figuring out the right approach as you go.
• You treat deployment as someone else’s problem
• You measure success by models trained, not by outcomes delivered.

Why SimplifyNext

We partner with governments and enterprises to shift from project delivery to product thinking. That means working on problems that genuinely matter — healthcare access, business licensing, workforce development — and being held accountable for outcomes, not just deliverables.

• 3+ years of backend development in Python, Go, or Java
• End-to-end LLM Agent production experience with depth in architecture design, hallucination handling, and tool-call fault tolerance
• Hands-on AI security knowledge — Prompt Injection, Jailbreak, malicious agent injection, tool misuse — with production-ready defensive solutions
• Production experience with at least one of LangChain, LlamaIndex, AutoGen, CrewAI, or LangGraph
• Proficiency with Docker, Kubernetes, and microservice architecture

• SAST/SCA or code auditing tool experience 
• LLM fine-tuning or local model deployment; security-domain fine-tuning is a strong plus
• Open source agent projects on GitHub or merged PRs to mainstream LLM frameworks
• CTF awards or CVE/CNVD submission records

We are seeking a talented and innovative Synthetic Data Engineer. In this role, you will design and implement domain-specific synthetic data generation pipelines, ensuring high-quality data management for training loops. Your expertise will drive the success of data processing and model training within the organization.

Responsibilities:

• Design domain-specific synthetic data generation (SDG) pipelines via self-instruct and constitutional prompting.
• Implement automated quality scoring and de-duplication systems.
• Manage data pipelines that feed directly into SFT and DPO training loops.

Qualifications:

• Proven experience building large-scale data pipelines (Airflow, Spark, Ray).
• Deep knowledge of prompt engineering for data generation.
• Familiarity with dataset distillation and bias mitigation.

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.

At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you.

Skills Required

• Pursuing a degree in Computer Science / Software Engineering
• Strong fundamentals in:
• Python
• data structures
• APIs / backend basics
• Hands-on experience building with modern AI tools, including:
• LLM APIs (OpenAI, Anthropic, or open-source models)
• Prompt engineering (structured prompts, iteration, testing)
• RAG (retrieval-augmented generation) or retrieval-based systems
• Working with real data (documents, APIs, datasets)
• Familiarity with:
• embeddings and semantic search
• vector databases (e.g., FAISS, Pinecone, etc.)
• frameworks like Lang Chain, Llama Index (or similar)
• Ability to explain your projects end-to-end (architecture, trade-offs, decisions)
• Curious, hands-on, and comfortable building in a fast-paced environment

This role is for candidates who have already built AI-powered applications, not just explored them

 Scope of Work

• Build and iterate on AI-powered workflows using LLMs
• Design and implement RAG pipelines with real-world data
• Integrate AI models with APIs, backend systems, and enterprise data sources
• Work directly with real customers to:
• understand use cases
• deploy conversational AI solutions
• support implementation and adoption
• Build POVs (proof of value), demos, and prototypes to showcase product capabilities
• Translate business problems into working AI solutions
• Collaborate across sales, product, and engineering teams
• Operate at the intersection of sales and technology, supporting:
• client conversations
• solution positioning
• technical storytelling
• Continuously improve systems across:
• accuracy
• latency

What’s in it for you?
Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NICEr!

Enjoy NICE-FLEX! 
At NICE, we work according to the NICE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere.

As a Backend Engineering Lead you'd be able to work on and solve many interesting challenges which we are facing, learn new ways of working, and help build delightful high quality products for our customers.  

Key Responsibilities

Technical Vision and Strategy

• Defines and communicates the technical vision and strategy for the engineering team, aligning it with overall business objectives.
• Evaluates emerging technologies and industry trends — including AI/ML capabilities, LLM-based tooling, and agentic frameworks — to inform technical roadmaps and architectural decisions.

Team Leadership and Mentorship

• Leads and mentors a team of engineers, fostering a culture of collaboration, innovation, and continuous learning.
• Provides guidance and support to team members, empowering them to grow both technically and professionally.
• Builds AI literacy across the team — ensuring engineers can effectively leverage AI-assisted development tools (code generation, automated review, test generation) while maintaining critical thinking about AI outputs.
• Coaches engineers on prompt engineering, AI pair-programming workflows, and when to trust vs. verify AI-generated code.

Project Management and Execution

• Manages technical projects from inception to delivery, overseeing planning, execution, and quality assurance processes.
• Coordinates with cross-functional teams, including product management, design, and QA, to ensure successful project outcomes.
• Incorporates AI-augmented estimation and planning tools where appropriate, while maintaining accountability for delivery commitments.

Architecture and Design

• Designs and implements scalable, maintainable, and extensible software architectures, considering factors such as performance, security, and scalability.
• Leads architectural discussions and collaborates with senior engineers to drive consensus on design decisions.
• Architects systems with AI integration patterns in mind — designing clean boundaries for AI/ML components, defining contracts between deterministic and probabilistic systems, and planning for model versioning, fallback strategies, and graceful degradation.

Technical Excellence

• Sets high standards for code quality, performance, and maintainability, and ensures adherence to best practices and coding standards.
• Conducts code reviews and provides constructive feedback to ensure the delivery of high-quality software solutions.
• Establishes guardrails and review standards for AI-generated code — ensuring it meets the same quality bar as human-written code, with particular attention to security, edge cases, and maintainability.
• Champions responsible AI practices: output validation, bias awareness, hallucination mitigation, and appropriate human-in-the-loop controls for critical paths.
  
  

Operational Ownership

• Takes end-to-end ownership of the systems the team builds — from deployment through production reliability, performance, and incident response.
• Drives operational maturity: SLOs/SLIs, alerting hygiene, runbook coverage, on-call readiness, and post-incident reviews that produce lasting improvements, not just action items.
• Ensures the team builds with production in mind from day one — observability, graceful degradation, and failure modes are first-class design concerns, not afterthoughts.
• Instils a "you build it, you run it" culture where engineers feel genuine accountability for what they ship and how it behaves under real-world conditions.

Problem-Solving and Decision-Making

• Demonstrates advanced problem-solving skills, leveraging deep technical expertise and critical thinking to address complex technical challenges.
• Makes informed decisions under uncertainty, weighing technical trade-offs and considering long-term implications.
• Knows when AI is the right tool for a problem and when it isn't — resists the pressure to "add AI" where simpler, more deterministic solutions are more reliable and cost-effective.
• Leverages AI-assisted analysis (log analysis, incident correlation, root cause detection) to accelerate debugging and reduce mean time to resolution.

Stakeholder Management and Communication

• Builds strong relationships with stakeholders, including product managers, business leaders, and other engineering teams, to understand requirements and priorities.
• Communicates technical concepts and project status effectively to both technical and non-technical stakeholders, adapting communication style as needed.
• Translates AI capabilities and limitations into business terms — sets realistic expectations around what AI can deliver, timelines for AI-powered features, and the ongoing cost of maintaining AI systems (compute, data quality, model drift).
• Educates stakeholders on the difference between demo-grade AI and production-grade AI, managing enthusiasm without stifling innovation.

Risk Management and Mitigation

• Identifies and mitigates technical risks proactively, anticipating potential issues and implementing contingency plans to minimize impact on project timelines and deliverables.
• Maintains a focus on security, privacy, and compliance requirements, ensuring that systems and processes adhere to relevant standards and regulations.

Continuous Improvement and Innovation

• Drives a culture of continuous improvement and innovation within the engineering team, encouraging experimentation, knowledge sharing, and adoption of new technologies.
• Promotes automation, tooling, and process enhancements to improve efficiency, reliability, and scalability of development workflows.
• Runs structured experiments with AI tools and workflows — measuring real impact on velocity, quality, and developer experience rather than relying on anecdotal evidence.
• Builds internal knowledge sharing around AI use cases, effective patterns, and lessons learned — creating a feedback loop that accelerates the team's AI maturity.
• Actively contributes to agentic AI workflows for automating repetitive engineering tasks (test generation, migration scripts, documentation, incident triage) while maintaining human oversight on critical decisions.
  
  

Leadership and Influence

• Leads by example, demonstrating integrity, accountability, and a commitment to excellence in all aspects of work.
• Inspires and motivates team members to achieve their full potential, fostering a positive and inclusive team culture.
• Positions the team as AI-forward without being AI-reckless — models the discipline of evaluating AI tools critically, adopting what works, and discarding what doesn't.
• Shapes the engineering organization's AI adoption narrative, contributing to company-wide standards, governance frameworks, and best practices for AI in production systems.

Role Specific Technical Competencies:

• Strong technical background in (AWS, Spring Boot, Kotlin, K8s, Microservices, Kafka, Istio, event-driven architecture).
• Exposure to Cloud Technologies, SRE (Site Reliability Engineering), and DevOps concepts with a focus on automation.

Our Ideal Candidate: 

• 10+ years of overall experience with the majority of this experience as an Engineering Lead or Manager.
• Experience working in Fintech / Financial organisations is an added advantage.
• At least 5 years of demonstrable leadership experience, at an individual team level and working across demographically distributed teams and organizational boundaries.
• Good experience in creating actionable strategies, with clear outcomes, and continuous measurement of progress.
• Ability to produce and communicate effective and insightful thought leadership on technical topics.
• Strong technical background in (AWS, Spring Boot, Kotlin, K8s, Microservices, Kafka, Istio, event-driven architecture).
• Exposure to Cloud Technologies, SRE (Site Reliability Engineering), and DevOps concepts with a focus on automation.
• Ability to take ownership and deliver results in a challenging client-facing environment.
• A degree in a relevant area of study would be helpful but not mandatory

Work you’ll do

As an AI Engineer at SimplifyNext, you will be part of a hands-on engineering team building real-world AI and machine learning solutions that create meaningful impact for clients across ASEAN. You will work closely with consultants, architects, and domain experts to translate business problems into deployable AI models, generative AI workflows, and intelligent automation components.

You will have the opportunity to experiment with modern AI frameworks, build prototypes, fine-tune models, and implement AI capabilities end-to-end—from data preparation to deployment. This role is designed for fresh graduates who want to build, break, learn, and innovate within a supportive environment grounded in consulting excellence and deep engineering capability.

Your responsibilities would include but not limited to:

AI & Machine Learning Development

· Build and train machine learning models using Python and modern ML frameworks

· Experiment with generative AI technologies (LLMs, embeddings, prompt engineering, RAG, agentic workflows)

· Support fine-tuning, optimisation, and evaluation of AI models

· Develop reusable AI components and microservices

Data Engineering & Preparation

· Collect, clean, and transform datasets for training and inference

· Perform exploratory data analysis to uncover patterns and insights

· Document data assumptions, limitations, and preprocessing logic

Solution Engineering

· Contribute to AI solution design, model selection, architecture discussions, and implementation approaches

· Integrate AI models into applications, APIs, and automation workflows

· Build proof-of-concepts (POCs) and accelerate client adoption of AI

Testing, Deployment & Delivery

· Conduct model validation, scenario testing, and UAT with internal and client stakeholders

· Support deployment of AI models on cloud platforms (AWS/GCP/Azure) or containerised environments

· Monitor performance and support continuous improvement post-deployment

Collaboration & Consulting Exposure

· Work with functional SMEs to understand business problems and AI opportunities

· Translate complex concepts into simple, understandable terms for non-technical audiences

· Participate in workshops, demos, and client discussions as part of project teams

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, AI, Data Science, or a related field.

• 0–3 years of AI development experience (Fresh graduates are welcome to apply)

• Strong foundation in Python, algorithms, and data structures

• Familiarity with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or HuggingFace

• Understanding of ML fundamentals: supervised/unsupervised learning, model evaluation, feature engineering

• Knowledge of cloud platforms (AWS, GCP, Azure) is a plus

• Familiarity with Git, REST APIs, or notebook-based development is beneficial

• Strong analytical thinking, curiosity, and problem-solving skills

• Passion for AI, experimentation, building things, and delivering quality work

Why Join Us

· Be part of a fast-growing consulting and technology firm driving AI, automation, and next-gen engineering

· Work on high-impact challenges across ASEAN, delivering real-world AI solutions

· Gain hands-on experience from day one with industry experts, architects, and consultants

· Contribute to innovation programmes, accelerators, and AI Centres of Excellence

· Grow rapidly through certifications, mentorship, structured enablement, and exposure to emerging AI technologies

· Join a supportive, high-trust culture that values creativity, experimentation, and continuous learning

Who We Are 

Build. Scale. Sustain.  

We are a global technology consultancy with a trademarked, AI-first engineering approach for accelerating the delivery of digital products, and revolutionizing platform modernization. We do the right thing, and we do it right. We're proud to be a World Economic Forum New Champion, and a B Corp-certified company. 

• We are small enough to care locally, big enough to deliver globally: 5 continents, 10 countries, +500 experts from +50 nationalities across the Americas, Europe and APAC
• We are robust and resilient: 100% independent and 0 debt
• We are entrepreneurs and passionate experts: We invest in what we believe genuinely and work as a collective intelligence 
• We are positive, courageous, caring, doers and committed to excellence 

About Gen-e2TM 
 
While the market is still largely AI-augmenting delivery, we have reinvented the SDLC to be AI First. Leveraging our 16 years expertise in digital transformation, our approach is a game-changer in productivity and quality, with a strong collaboration between IA generative and our best Talents: 

• We now generate 95% of the entire product — code, documentation, infrastructure as code, and even design powered by GitHub Copilot. 
• The quality consistently exceeds the output of our best traditional engineering teams.
• A product repository houses all product artefacts, giving AI full project context for higher-quality generation.
• A library of rules and prompts defines coding standards, design principles, and security guidelines, ensuring enterprise-grade quality and scalability. 

With Gen-e2TM, we deliver end-to-end products 2–3× faster than traditional approaches, while raising the bar for engineering excellence. 

YOUR ROLE 

At Palo IT, every engineer is AI-native. As a Software Engineer (AI-Native), you will design, build, and deliver production-grade applications while actively using AI and Generative AI as part of your daily engineering workflow. 

You will work primarily with modern fullstack technologies for frontend and backend, with exposure to cloud platforms (Azure, AWS, GCP). You will apply Palo IT's Gen-E2 methodology to accelerate delivery, improve code quality, and build scalable, secure applications. 

Key Responsibilities 

Software Engineering & Development 

• Design, build, and maintain full stack applications using modern frameworks (ReactJS, NodeJS, Java, Python or equivalent)
• Develop scalable, reliable, and secure applications following modern software engineering practices.
• Implement CI/CD automation pipelines and understand DevOps workflows.
• Ensure code quality through testing, code reviews, and performance optimisation. 

AI-Native Engineering (Core Expectation) 

• Use Generative AI coding tools (e.g., GitHub Copilot, Cursor) as a first-class engineering assistant for: 
• Code scaffolding and refactoring
• Code generation and optimisation
• Test-cases and documentation generation
• Build applications through AI-driven development practices, including: 
• AI-assisted debugging and troubleshooting
• Intelligent code completion and pattern recognition
• Automated documentation generation
• Apply prompt engineering best practices for reliable, repeatable engineering outcomes.
• Validate GenAI output (determinism checks, guardrails, fallback logic). 

Collaboration & Delivery 

• Collaborate with project teams, product managers, and designers to deliver high-quality solutions.
• Contribute to Gen-E2 practices, reusable accelerators, and internal playbooks.
• Support solution discussions and technical discovery when required. 

Must-Have Experience 

• 3+ years of hands-on software development experience. Preferred technologies include ReactJS for frontend development and NodeJS/Java for backend development.
• Understanding of relational and non-relational databases.
• Experience with testing frameworks and code quality practices.
• Strong understanding of common programming patterns and principles.
• Demonstrated use of AI tools in day-to-day engineering work (not just theoretical exposure). 

AI-Native & Gen-E2 Skills (Required) 

• Hands-on experience with GitHub Copilot or equivalent AI coding assistants.
• Ability to build and evolve applications using GenAI assistance.
• Strong understanding of prompt engineering for technical use cases.
• Experience validating and controlling GenAI outputs (hallucination handling, code review of AI-generated code).
• Critical thinking to verify AI-generated code and solutions. 

Good to Have 

• Experience with cloud computing platforms (Azure, AWS, GCP).
• Experience with solution architecture principles.
• Exposure to AI/ML services and frameworks.
• Native mobile development (iOS, Android) or hybrid mobile development (Flutter, React Native). 

What Success Looks Like at Palo IT 

• You deliver high-quality, production-grade applications using AI-native practices.
• You leverage AI tools effectively while maintaining code quality and best practices.
• You contribute to Palo IT's Gen-E2 maturity across projects and teams.
• You continuously learn and adapt to the rapidly evolving AI landscape. 

We will be prioritizing applicants who have a current right to work in Singapore, and do not require sponsorship of a visa. 

More About PALO IT 

We’re eager to adapt to change, learn from our experiences and move to meet our planet’s urgent needs. We are continuously taking action to: 

• Become a climate net-zero company  
• Deliver projects with a positive impact
• Train 100% of our workforce on impact   
• Achieve B Corp certification among all our offices across the globe   
• Continuously measure & improve employee happiness  

Our clients are amongst the world's most successful companies. We innovate with both established Fortune 1000s, SMEs and start-ups who aim to make an impact, become global leaders and address the world's most complex challenges. 

What We Offer 

• Stimulating working environments
• Unique career path
• International mobility  
• Internal R&D projects
• Knowledge sharing
• Personalized training
• Entrepreneurship & intrapreneurship 

For more on our team culture and benefits, check out our careers page.

PALO IT Singapore is an equal opportunity employer. Employment decisions will be based on merit, qualifications and abilities. Palo IT SG does not discriminate in employment opportunities or practices on the basis of race, colour, religion, sex, sexuality, national origin, age, disability, marital status or any other characteristics protected by law.

Protecting your privacy and the security of your data are longstanding top priorities for Palo-IT.

Your personal data will be processed for the purposes of managing Palo-IT’s recruitment related activities, which include setting up and conducting interviews and tests for applicants, evaluating and assessing the results, and as is otherwise needed in the recruitment and hiring processes.

Please consult our Privacy Notice to know more about how we collect, use, and transfer the personal data of our candidates. Here you can find how you can request for access, correction and/or withdrawal of your Personal Data.

Who We Are

Build. Scale. Sustain.

We are a global technology consultancy with a trademarked, AI-first engineering approach for accelerating the delivery of digital products, and revolutionizing platform modernization. We do the right thing, and we do it right. We're proud to be a World Economic Forum New Champion, and a B Corp-certified company.

• We are small enough to care locally, big enough to deliver globally: 5 continents, 10 countries, +500 experts from +50 nationalities across the Americas, Europe and APAC
• We are robust and resilient: 100% independent and 0 debt
• We are entrepreneurs and passionate experts: We invest in what we believe genuinely and work as a collective intelligence
• We are positive, courageous, caring, doers and committed to excellence

About Gen-e2TM

While the market is still largely AI-augmenting delivery, we have reinvented the SDLC to be AI First. Leveraging our 16 years expertise in digital transformation, our approach is a game-changer in productivity and quality, with a strong collaboration between IA generative and our best Talents:

• We now generate 95% of the entire product — code, documentation, infrastructure as code, and even design powered by GitHub Copilot.
• The quality consistently exceeds the output of our best traditional engineering teams.
• A product repository houses all product artefacts, giving AI full project context for higher-quality generation.
• A library of rules and prompts defines coding standards, design principles, and security guidelines, ensuring enterprise-grade quality and scalability.

With Gen-e2TM, we deliver end-to-end products 2–3× faster than traditional approaches, while raising the bar for engineering excellence.

YOUR ROLE

At Palo IT, senior engineers are expected to be AI-native by default. As a Senior Software Engineer (AI-Native), you will lead the development of complex features and modules while guiding team members on technical decisions and AI-assisted development practices.

You will partner with Tech Leads, Architects, and cross-functional teams to deliver scalable solutions. You will apply Palo IT's Gen-E2 methodology to accelerate delivery and improve engineering quality.

Key Responsibilities

Software Engineering & Development (Senior Scope)

• Lead the development of complex features, modules, and components.
• Design high-performance, scalable solutions using AI-powered approaches.
• Ensure code quality through testing, code reviews, and AI-assisted analysis.
• Understand DevOps workflows and implement CI/CD automation pipelines.
• Establish best practices on code quality and performance within project scope

AI-Native Engineering (Core Expectation)

• Use Generative AI coding tools (e.g., GitHub Copilot, Cursor) as a first-class engineering assistant for code generation, optimisation, and problem-solving.
• Guide team members on effective use of AI tools and prompt engineering techniques.
• Establish AI/GenAI best practices within project scope, including output validation and guardrails.
• Leverage AI tools to troubleshoot and resolve technical issues efficiently.
• Stay current with emerging AI technologies and development practices.

Collaboration & Technical Guidance

• Mentor junior and mid-level engineers on technical skills and AI-assisted workflows.
• Partner with Tech Leads and Architects to guide technical decisions within projects.
• Collaborate with product managers and designers to deliver high-quality solutions.
• Contribute to Gen-E2 practices, reusable accelerators, and internal playbooks.
• Support presales and architecture discussions when required.

Must-Have Experience

• 5+ years of hands-on software development experience
• Deep technological expertise and a strong software development background.
• Experience with solution architecture.
• Experience in developing scalable, reliable, and secure applications.
• Preferred technologies include ReactJS for frontend development and NodeJS/Java/Python for backend development.
• Strong understanding of common programming patterns and principles.
• Demonstrated use of AI tools in day-to-day engineering work (not just theoretical exposure).

AI-Native & Gen-E2 Skills (Required)

• Hands-on, daily use of AI coding assistants (GitHub Copilot or equivalent).
• Strong understanding of prompt engineering principles for optimal AI tool interaction.
• Experience validating and controlling GenAI outputs (hallucination handling, code review of AI-generated code).
• Critical thinking to validate and verify AI-generated code and solutions.

Good to Have

• Team leadership experience.
• Experience with AI/ML services and frameworks.
• Experience with cloud computing platforms (Azure, AWS, GCP).
• Native mobile development (iOS, Android) or hybrid mobile development (Flutter, React Native).

What Success Looks Like at Palo IT

• You lead development of complex features with AI-native practices.
• You guide and mentor team members on technical skills and AI tools.
• You establish best practices within your projects.
• You contribute to Palo IT's Gen-E2 maturity across projects.

We will be prioritizing applicants who have a current right to work in Singapore, and do not require sponsorship of a visa.

More About PALO IT

We’re eager to adapt to change, learn from our experiences and move to meet our planet’s urgent needs. We are continuously taking action to:

• Become a climate net-zero company
• Deliver projects with a positive impact
• Train 100% of our workforce on impact
• Achieve B Corp certification among all our offices across the globe
• Continuously measure & improve employee happiness

Our clients are amongst the world's most successful companies. We innovate with both established Fortune 1000s, SMEs and start-ups who aim to make an impact, become global leaders and address the world's most complex challenges.

What We Offer

• Stimulating working environments
• Unique career path
• International mobility
• Internal R&D projects
• Knowledge sharing
• Personalized training
• Entrepreneurship & intrapreneurship

For more on our team culture and benefits, check out our careers page

PALO IT Singapore is an equal opportunity employer. Employment decisions will be based on merit, qualifications and abilities. Palo IT SG does not discriminate in employment opportunities or practices on the basis of race, colour, religion, sex, sexuality, national origin, age, disability, marital status or any other characteristics protected by law.

Protecting your privacy and the security of your data are longstanding top priorities for Palo-IT.

Your personal data will be processed for the purposes of managing Palo-IT’s recruitment related activities, which include setting up and conducting interviews and tests for applicants, evaluating and assessing the results, and as is otherwise needed in the recruitment and hiring processes.

Please consult our Privacy Notice to know more about how we collect, use, and transfer the personal data of our candidates. Here you can find how you can request for access, correction and/or withdrawal of your Personal Data.

Who We Are

At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more.

About the Opportunity

What You’ll Be Doing 

What We Look For In You 

Nice to Haves

Perks & Benefits

• Competitive total compensation package
• L&D programs and Education subsidy for employees' growth and development
• Various team building programs and company events
• Wellness and meal allowances
• Comprehensive healthcare schemes for employees and dependants
• More that we love to tell you along the process!

Please note that Hong Kong is a group-level service hub, and OKX does not carry on a business of operating a virtual asset trading platform in Hong Kong.

OKX will be prioritising applicants who have a current right to work in Singapore, and do not require OKX's sponsorship of a visa.

Who We Are

At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more.

About the Opportunity

What You’ll Be Doing 

What We Look For In You 

Nice to Haves

Perks & Benefits

• Competitive total compensation package
• L&D programs and Education subsidy for employees' growth and development
• Various team building programs and company events
• Wellness and meal allowances
• Comprehensive healthcare schemes for employees and dependants
• More that we love to tell you along the process!

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. 

Who We Are 

Build. Scale. Sustain.  

We are a global technology consultancy with a trademarked, AI-first engineering approach for accelerating the delivery of digital products, and revolutionizing platform modernization. We do the right thing, and we do it right. We're proud to be a World Economic Forum New Champion, and a B Corp-certified company. 

• We are small enough to care locally, big enough to deliver globally: 5 continents, 10 countries, +500 experts from +50 nationalities across the Americas, Europe and APAC
• We are robust and resilient: 100% independent and 0 debt
• We are entrepreneurs and passionate experts: We invest in what we believe genuinely and work as a collective intelligence 
• We are positive, courageous, caring, doers and committed to excellence 

About Gen-e2TM 
 
While the market is still largely AI-augmenting delivery, we have reinvented the SDLC to be AI First. Leveraging our 16 years expertise in digital transformation, our approach is a game-changer in productivity and quality, with a strong collaboration between IA generative and our best Talents: 

• We now generate 95% of the entire product — code, documentation, infrastructure as code, and even design powered by GitHub Copilot. 
• The quality consistently exceeds the output of our best traditional engineering teams.
• A product repository houses all product artefacts, giving AI full project context for higher-quality generation.
• A library of rules and prompts defines coding standards, design principles, and security guidelines, ensuring enterprise-grade quality and scalability. 

With Gen-e2TM, we deliver end-to-end products 2–3× faster than traditional approaches, while raising the bar for engineering excellence. 

YOUR ROLE AND RESPONSIBILITIES 

As a member of an Agile delivery team, you will be responsible for the design and execution of test automation and quality engineering activities across Web, API, Mobile, Cloud, and Data platforms. You will define and implement test strategies with the team in applying automation, exploratory, performance, and data pipeline testing practices effectively. 

You will: 

• Be responsible for building and maintaining scalable automation frameworks for Web, API, Mobile, Cloud, and Data systems.
• Define and execute test strategies, balancing automation, exploratory, performance, and data testing.
• Implement automation scripts using tools such as Selenium, Playwright, Cypress, Appium, and Katalon.
• Design and execute tests for data platforms, including ETL pipelines, data quality, schema validation, and transformation logic.
• Apply structured test approaches for data engineering workflows (batch vs. streaming, ingestion, transformation, storage, and consumption).
• Integrate automated tests into CI/CD pipelines and ensure reliable execution.
• Perform exploratory testing to uncover gaps not easily detected by automation.
• Support performance, scalability, and reliability testing using tools like JMeter, Gatling, or k6.
• Apply AI-powered QA tools and prompt engineering techniques to accelerate test creation and analysis.
• Collaborate closely with developers, product owners, and business analysts to ensure requirements are testable and automation-ready.

WHO YOU ARE 

• Strong experience in test automation, framework design, and quality engineering.
• Solid background in functional and automation testing across Web, API, Mobile, Cloud, and Data platforms.
• Strong in hands-on coding in Java, JavaScript, Python, or similar languages for automation.
• Hands-on experience in mobile automation testing with Appium and/or Katalon.
• Exposure to performance and load testing.
• Experience with AI/ML-driven test tools and basic prompt engineering.
• Strong background in exploratory testing and modern test design techniques.
• Good understanding of Agile/Scrum delivery.
• Familiarity with CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI) and cloud-native testing (AWS, Azure, GCP).
• Excellent collaboration and problem-solving skills. 

BONUS SKILLS 

• Knowledge of data platform & data engineering pipeline testing (ETL validation, streaming, data quality).
• Experience with big data test strategies and analytics validation. 

We will be prioritizing applicants who have a current right to work in Singapore, and do not require sponsorship of a visa. 

More About PALO IT 

We’re eager to adapt to change, learn from our experiences and move to meet our planet’s urgent needs. We are continuously taking action to: 

• Become a climate net-zero company  
• Deliver projects with a positive impact
• Train 100% of our workforce on impact   
• Achieve B Corp certification among all our offices across the globe   
• Continuously measure & improve employee happiness  

Our clients are amongst the world's most successful companies. We innovate with both established Fortune 1000s, SMEs and start-ups who aim to make an impact, become global leaders and address the world's most complex challenges. 

What We Offer 

• Stimulating working environments
• Unique career path
• International mobility  
• Internal R&D projects
• Knowledge sharing
• Personalized training
• Entrepreneurship & intrapreneurship 

For more on our team culture and benefits, check out our careers page.

PALO IT Singapore is an equal opportunity employer. Employment decisions will be based on merit, qualifications and abilities. Palo IT SG does not discriminate in employment opportunities or practices on the basis of race, colour, religion, sex, sexuality, national origin, age, disability, marital status or any other characteristics protected by law.

Protecting your privacy and the security of your data are longstanding top priorities for Palo-IT.

Your personal data will be processed for the purposes of managing Palo-IT’s recruitment related activities, which include setting up and conducting interviews and tests for applicants, evaluating and assessing the results, and as is otherwise needed in the recruitment and hiring processes.

Please consult our Privacy Notice to know more about how we collect, use, and transfer the personal data of our candidates. Here you can find how you can request for access, correction and/or withdrawal of your Personal Data.