Lead Engineer Contractor (Full-Stack)Contract

About Eightgen

Eightgen is an AI services company that partners with founders, CIOs, and CXOs to transform ideas into working products. We help startups and enterprises ship AI automation at scale—from intelligent workflows and custom AI agents to enterprise-grade applications.

Our Values

Integrity & Ethics We conduct business with honesty and transparency. We do what's right for our clients, our team, and our partners—even when it's harder. We handle data responsibly and respect the trust placed in us.

Quality & Accountability We take ownership of our work and deliver on our commitments. We build software we're proud of, with attention to detail and a commitment to excellence. When we make mistakes, we acknowledge them and fix them.

Trust & Autonomy We hire talented people and give them the freedom to do their best work. We communicate openly, share context generously, and trust each other to make good decisions.

Inclusion & Belonging We are committed to building a diverse team where everyone feels welcome, respected, and heard. Different backgrounds, perspectives, and experiences make us stronger.

We are a fully remote team that values outcomes over hours and collaboration over hierarchy.

The Role

As a Lead Engineer, you will be a hands-on technical leader — spending roughly 70% of your time writing and shipping code, and the remaining 30% providing technical direction, conducting code reviews, and mentoring engineers on the team.

You will own the design of the services and features your team builds, make pragmatic technical decisions, and ensure the team consistently ships high-quality software. This is not a management role, and it is not an architect role either — we want a strong individual contributor who can design a system end-to-end, build it, and lead a small team through it, and who is as comfortable on a whiteboard as they are in a pull request.

We embrace AI-augmented development. You will leverage AI coding assistants (GitHub Copilot, Cursor, Claude Code, or similar) as integral tools in your workflow and encourage the same in your team — not as a crutch, but as a force multiplier.

Our AI-Augmented Development Philosophy

We believe the most effective engineers in 2025 and beyond are those who:

1. Master the fundamentals — Deep understanding of Python, databases, system design, and software engineering principles remains essential

2. Leverage AI as a collaborator — Use AI tools to accelerate routine tasks, generate boilerplate, explore solutions, and augment productivity

3. Maintain quality ownership — Treat AI output as a starting point, not a final answer. Review, test, and refine all code before it reaches production

4. Think architecturally — AI tools are excellent at implementation but require human guidance for design decisions, trade-off analysis, and system-level thinking

5. Continuously optimize workflows — Experiment with prompts, tools, and techniques to maximise the value of AI assistance

Key Responsibilities

• Lead technical delivery — own the design and delivery of the services your team is building, define standards within that scope, and ensure the team ships reliable, maintainable software on time

• Design systems end-to-end — produce technical designs, data models, and API contracts for the features and services you own, with a clear eye on scalability, evolution, and avoiding crippling technical debt

• Stay hands-on — contribute directly to the codebase across backend services, APIs, data pipelines, and where needed, frontend components — leading by example, not just by review

• Raise the engineering bar — conduct thorough code and design reviews, provide actionable feedback, and actively grow the technical capability of engineers around you

• Care about the non-functional side — bake performance, security, reliability, and observability into the work your team owns, not as an afterthought

• Make pragmatic trade-off calls — weigh build-vs-buy, speed-vs-correctness, and short-term-vs-long-term decisions within your area, and clearly articulate the reasoning

• Collaborate cross-functionally — partner with product managers, designers, and business stakeholders to translate ambiguous requirements into well-scoped, well-sequenced engineering work

• Champion best practices — establish and enforce coding standards, testing strategies, CI/CD practices, and observability across the stack

• Leverage AI tools effectively — model effective AI-augmented development practices for the team while maintaining critical oversight of AI-generated output

Required Qualifications

Technical Skills

• 7+ years of professional software engineering experience, with a strong backend bias and solid full-stack capability

• Solid system design ability — has designed and shipped non-trivial features or services end-to-end: data flow, API contracts, failure modes, and day-2 operational concerns

• Deep Python expertise — production experience with FastAPI or Django, async patterns, type hints, and modern Python best practices

• Strong frontend competency — ability to build and own React/TypeScript features end-to-end, even if backend is your primary strength

• Solid SQL and data modelling skills — schema design, query optimisation, indexing strategies, and experience with PostgreSQL or similar

• Cloud platform experience — production experience on Google Cloud Platform (Cloud Run, Cloud SQL, GCS) or equivalent AWS/Azure services, with a practical grasp of IAM, secrets, and cost trade-offs

• Distributed systems knowledge — comfort with queues, caching, background task processing, event-driven patterns, and API design at scale

• Demonstrated technical leadership — has led engineering teams or workstreams through code reviews, design reviews, on-call/operational ownership, or hiring and mentoring

• Strong Git and delivery discipline — branching strategies, PR hygiene, CI/CD pipelines, and collaborative development workflows

AI-Assisted Development Skills

• Hands-on experience with AI coding assistants such as GitHub Copilot, Cursor, Claude Code, or similar tools in day-to-day workflows

• Ability to guide teams on AI tool adoption — helping teammates use AI tools effectively and critically, not blindly

• Strong code review instincts for AI-generated output — able to spot subtle bugs, security issues, or architectural missteps in AI-assisted code

Preferred Qualifications

• Experience building or leading multi-tenant SaaS platforms

• Background in data-intensive applications — pipelines, analytics, or enterprise integrations

• Familiarity with LLM/AI integrations (OpenAI, Anthropic, LangChain) and agentic workflow patterns

• Experience with ClickHouse, BigQuery, or other analytical databases

• Prior work in early-stage or consulting environments where scope evolves quickly and engineers wear multiple hats

Technical Environment

Our primary stack is listed first in each row, but we equally value experience with comparable tools — the underlying skills transfer.

Engagement Details

• Contract Duration: Initial 3-month engagement
• Extension: Strong opportunity to extend for additional 6+ months based on performance and project needs
• Work Arrangement: Fully remote
• Start Date: Immediately