Technical Lead/Architect

Arionkoder is an AI consulting firm helping companies build, embed, and own AI systems that drive real business outcomes. We combine Product Development, Artificial Intelligence, and Team Augmentation to craft digital products and solutions that create lasting impact — guided by a human-centric approach and a commitment to pushing the boundaries of what technology can do.

We're hiring a Software Architect & Technical Lead to own the end-to-end design of a complex software product and lead the team that builds it. The role spans the full architectural surface — data, services, integrations, infrastructure, security, reliability — and sits at the intersection of engineering, product, and the customer environments the product runs inside.

This is a hands-on architect role, not a diagrams-and-handoffs role  but diagrams and decision records are part of the job. You communicate architecture clearly through C4 models (context, container, component) and lightweight ADRs that capture decisions, context, and trade-offs so the team doesn't re-litigate them six months later. You also write code on critical paths, review designs and PRs, take ownership when the parts you designed misbehave in production, and push back when a feature request would compromise the architecture.

AI is core to this role, not adjacent to it. You’ve designed and shipped production systems where LLMs are load-bearing, and you know what that takes: retrieval and context design, evaluation, guardrails, cost and latency budgets, and failure modes that don’t show up in a demo. You also use AI as your daily engineering layer. You wield it with judgment, and you set the patterns your team follows.

Beyond owning the design, you lead the team that delivers it. You take a single, important objective and drive it to completion  turning it into a technical plan, sequencing the work, keeping the team aligned on the goal and the reasoning behind it, unblocking people, and owning whether it ships at the right quality and pace. You're comfortable in ambiguity. You can join a product mid-flight, form a sharp view of what's load-bearing and what's incidental, and propose a direction the team can rally behind.

You treat AI-augmented engineering as a force multiplier you wield with judgment neither a gimmick nor a substitute for thinking.

• Required Qualifications
• 10+ years building production distributed systems, with at least 3 years in a Staff, Principal, or Architect role
• Strong fluency in JavaScript/TypeScript, React, and Node.js; comfortable reading and contributing across multiple languages and stacks

Deep AWS architecture expertise: has designed and operated non-trivial multi-tenant systems across compute (ECS/EKS/Lambda), data (RDS, DynamoDB, S3), networking (VPC, ALB, PrivateLink), and identity (IAM, KMS, Secrets Manager); able to reason about cost, blast radius, and failure modes at the service level, not just the diagram level

Writing code on critical paths, reviewing designs and PRs, taking ownership when the parts you designed misbehave in production, and pushing back when a feature request would compromise the architecture

Preferable

Experience with Python

Communicating architecture clearly through C4 models (context, container, component) and lightweight ADRs that capture decisions, context, and trade-offs so the team doesn't re-litigate them six months later

Hands-on production experience with at least one AI/LLM-powered system, including a real understanding of retrieval, prompt/context design, cost, and failure modes

Experience integrating with at least three meaningful third-party platforms in production (e.g. Slack, GitHub, Atlassian, Google Workspace, Salesforce, Stripe, IDE extensions, MCP servers)

What this person will own and do day-to-day

• Architecture and technical direction
• Own the end-to-end architecture of the product: data model, services, integrations, infrastructure, security, and reliability. Communicate architecture through C4 diagrams (context, container, component, and code where it adds value) that stay current with the system. Author and curate ADRs (architectural decision records) that capture context, options, trade-offs, and consequences for every load-bearing decision. Set the architectural guardrails (boundaries, contracts, SLAs) that let the team move fast without re-litigating foundational decisions. Make build/buy/integrate decisions across platforms, frameworks, third-party services, and infrastructure. Define and evolve the canonical schema, versioning model, and core abstractions of the product.
• Hands-on engineering
• Write production code on critical paths, especially where the architectural risk is highest. Lead design reviews and review PRs on load-bearing parts of the system. Prototype hard problems quickly to de-risk decisions before the team commits. Profile, debug, and stabilize systems under real production conditions.
• Reliability, security, and enterprise readiness
• Drive the architecture for deployment, data residency, and audit. Lead the response to systemic reliability issues and convert them into durable architectural improvements. Define the access control, permissions, and audit-log model across the product. Own incident postmortems on systemic issues and translate them into roadmap-level changes.
• Cross-functional and engineering collaboration
• Partner with engineering leadership to translate architecture into shippable increments. Work directly with Product on what's architecturally feasible inside the current quarter vs. what's a quarter-out investment. Mentor engineers on systems thinking, trade-off analysis, and writing for design clarity. Represent the product's architecture to enterprise customers during technical evaluations and security reviews.
• AI-augmented engineering practice
• Use modern AI engineering tooling (IDE agents, CLI assistants, MCP servers) as a daily working layer. Set the team's working patterns for spec-driven development, evaluation gates, and AI-assisted code review. Distinguish where AI accelerates the work and where it introduces risk; encode that distinction in the delivery process.

About us

In 2010, our founders dreamed up a company that could positively impact the world. Since then, we've been in permanent evolution: from business consulting to innovation and design, and now to building amazing digital products powered by AI. We scaled globally, launched AI Labs and Reshape Studios, and claimed our space as an AI consulting firm — helping organizations move from pilots to production through accountable AI.

Today, we're expanding our impact across industries, driving real AI adoption through accountability, governance, and value at scale. Dreamers first, builders always.