AI-Native Software Engineer Lead at KMS Technology

Ho Chi Minh City, , Vietnam -

Full Time

Start Date

Immediate

Expiry Date

05 Jul, 26

Salary

0.0

Posted On

06 Apr, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI-native SDLC, Multi-agent systems, Prompt engineering, Python, TypeScript, JavaScript, Java, Go, Software architecture, LLM API integration, RAG architectures, Agent evaluation, Orchestration frameworks, MLOps, System decomposition, API design

Industry

Software Development

Description

Company Description KMS Technology is a strategic engineering company helping businesses turn bold ideas into high-impact solutions-faster. Founded in 2009 as a U.S.-based services company, we’ve grown into a global organization with locations in the US, Vietnam, Mexico and Poland. KMS is trusted globally for the quality of our engineering and consulting services. We bring deep expertise in product development and quality assurance, Data & AI-native engineering, and delivery excellence to every engagement. Our mission is to help customers build what’s next—accelerating innovation, crafting brilliant solutions, and creating real-world impact. At KMS, we believe sustainable growth is built on the success of our clients and employees, and in making a lasting contribution to our communities. More about KMS Technology: Website: https://kms-technology.com LinkedIn: https://www.linkedin.com/company/kms-technology Job Description AI-Native Engineering Practice - Technical Ownership: Own and continuously evolve KMS's AI-native SDLC operating model at KMS: agent workflow designs, verification gates, context management standards, and eval frameworks Build and lead multi-agent systems using orchestration layers such as Claude Code, GitHub Copilot Workspace, Cursor, LangGraph, CrewAI, or equivalent — from prototype to production In collaboration with the Director of Engineering, contribute to and help maintain KMS's AI toolchain selection criteria — evaluating tools with engineering rigor, not hype — and publishing internal guidance on when AI helps and when it hurts Establish prompt engineering standards, agent evaluation (evals) loops, and AI output quality gates across the delivery organization Capability & Standards Leadership Prior experience in a lead, principal, or staff engineer role with demonstrated cross-team influence Experience in outsourcing, consulting, or multi-client delivery environments Track record of building or leading an internal community of practice, guild, or AI adoption program Develop and continuously evolve KMS's AI-native SDLC playbook — standards, workflow templates, case studies, and guardrails that delivery teams can adopt immediately Design and lead internal upskilling programs (workshops, pairing) that move engineers from AI-assisted to AI-native working patterns Track the AI capability frontier — model improvements, new agent frameworks, emerging risks — and translate signals into timely updates to KMS's practices Client Delivery Work closely alongside KMS Delivery Teams — as an AI transformation advisor and execution partner — identifying the highest-value automation opportunities across the SDLC and coordinating with the team to bring them to life Design and deploy agent-orchestrated workflows tailored to each client's stack, team maturity, and delivery context — with measurable ROI Build business cases for AI-native adoption with clients and account managers, framing the value in terms of velocity, quality, and cost Represent KMS's AI-native engineering capabilities in client conversations, QBRs, and RFP responses — acting as a credible technical authority Qualifications Core Engineering Foundation 8+ years of professional software engineering, with a proven track record of leading technical initiatives that span multiple teams or systems Deep hands-on experience across the full SDLC: from requirements and architecture through testing, deployment, and production operations Demonstrated ability to lead technical direction — setting standards, reviewing architecture decisions, and influencing without direct authority Strong command of software architecture principles: system decomposition, API design, scalability, observability, and failure mode reasoning Proficiency in at least one primary language: Python, TypeScript/JavaScript, Java, .Net or Go — with experience across multiple layers of the stack AI & Agentic Systems Fluency Proven, production-grade experience with AI coding agents as a core part of your daily workflow Strong understanding of LLM API integration in production: context window management, latency and cost tradeoffs, model selection criteria, fallback strategies, and output reliability patterns Experience or strong interest in multi-agent orchestration patterns: task decomposition, agent communication, tool use, memory, and eval loops Working knowledge of RAG architectures, embedding strategies, and how to ground AI agents in domain-specific, proprietary knowledge bases Ability to design and run AI evals: you can define quality metrics, build evaluation datasets, detect regressions, and use quantitative signals to improve agent behaviour over time Nice to have Experience with agentic frameworks: LangGraph, CrewAI, AutoGen, or similar orchestration patterns MLOps knowledge: model deployment, monitoring, drift detection, A/B testing in production Familiarity with AI security risks: prompt injection, adversarial inputs, data leakage in agentic contexts Additional Information Perks You'll Enjoy Working in one of the Best Places to Work in Vietnam Building large-scale & global software products Working & growing with Passionate & Talented Team Diverse careers opportunities with Software Services, Software Product Development, IT Solutions & Consulting Flexible working time Various training on hot-trend technologies, best practices and soft skills Company trip, big annual year-end party every year, team building, etc. Fitness & sport activities: football, tennis, table-tennis, badminton, yoga, swimming… Joining community development activities: 1% Pledge, charity every quarter, blood donation, public seminars, career orientation talks,… Free in-house entertainment facilities (foosball, ping pong, gym…), coffee, and snack (instant noodles, cookies, candies…) And much more, join us and let yourself explore other fantastic things! Talent Acquisition Team ► Hotline: (84) 938 118 997 ► Email: [email protected]

Responsibilities

You will lead the AI-native engineering practice by designing agent-orchestrated workflows and establishing SDLC standards. Additionally, you will act as an AI transformation advisor to delivery teams and clients to drive measurable ROI through automation.