AI Architect / Lead Engineer (Agentic GenAI)

We're hiring a AI architect / lead engineer to design and deliver agentic, LLM-powered systems for our clients. This is a hands-on, client-facing role focused primarily on generative AI and agentic workflows, with traditional machine learning as a bonus, not the core.

Role Overview

You will own the end-to-end technical design and implementation of GenAI solutions: from discovery and use-case shaping, through architecture and prototyping, to productionization and reusable patterns for our consulting teams. The emphasis is on agentic systems, tool-using agents, and workflow automation across our clients' existing platforms and data.

Key Responsibilities

• Lead technical discovery with clients to identify high-value GenAI and agent use cases tied to concrete business outcomes.
• Translate fuzzy ideas into clear solution designs, user journeys, and MVP scopes that can be quickly validated.
• Design end-to-end architectures for GenAI applications: frontend, backend/APIs, orchestration, LLM providers, vector databases, and integrations with enterprise systems and SaaS platforms.
• Build and maintain LLM-powered services: conversational copilots, workflow agents, embedded assistants, and task-specific bots for internal and external users.
• Design, implement, and operate agentic systems: planner/executor patterns, tool-using agents, and (where appropriate) multi-agent patterns for complex workflows.
• Integrate agents with real tools and systems (REST/GraphQL APIs, internal microservices, workflow engines, data platforms), including authentication, authorization, and auditing.
• Establish standards for prompt and system design, tool schemas, safety guardrails, observability, and reliability for GenAI and agentic solutions across projects.
• Mentor engineers and consultants, review designs and code, and drive best practices and shared patterns across multiple client engagements.
• Create reusable reference architectures, templates, and frameworks that accelerate future GenAI and agent projects.
• Contribute to thought leadership via internal enablement and external content (talks, blog posts, OSS) when appropriate.

Must-Have Qualifications

Experience and Background

• 6–10+ years of professional experience as a software engineer, backend engineer, or solutions/enterprise architect.
• Proven track record shipping production-grade backend systems and APIs (not just prototypes or research notebooks).
• Strong programming skills in at least one major backend language (e.g., Python, TypeScript/Node, Java/Scala), with solid engineering practices (testing, code review, CI/CD, version control).
• Demonstrated experience with agentic engineering practices — i.e., AI-native development workflows such as using LLM-powered coding assistants, AI-driven code generation, and prompt-driven prototyping as core parts of the software development lifecycle.
• Significant experience with at least one major cloud provider (AWS, Azure, or GCP), including designing and operating services using containers and/or serverless, logging, metrics, and alerting.

GenAI / LLM Expertise

• Hands-on experience building applications on top of hosted LLMs (e.g., OpenAI, Azure OpenAI, Anthropic, AWS Bedrock, Gemini, or open-source models via hosted platforms).
• Strong prompt and system message design skills for chats, copilots, and task automation, including iterative refinement and evaluation.
• Familiarity with embeddings and vector databases (e.g., Pinecone, Weaviate, pgvector, Redis, OpenSearch) and retrieval-augmented generation (RAG) patterns: chunking strategies, metadata, and relevance evaluation.
• Understanding of GenAI-specific evaluation concerns: hallucinations, safety controls, relevance, and UX patterns for user control and correction.

Agentic Systems and Tools

• Prior experience building agentic systems, including:

• Planner/executor patterns and multi-step reasoning flows.

• Tool-using agents that call external APIs, services, and workflows.

• (Optional but valued) Multi-agent setups such as supervisor/worker or specialist agents.

• Practical experience with at least one agent/orchestration framework or pattern (e.g., LangGraph, LangChain agents, Semantic Kernel, custom orchestrators, or major LLM providers' tool/agent APIs), or workflow automation platforms with AI/agent capabilities (e.g., n8n).

• Ability to design robust tools: clear schemas, input/output contracts, validation, rate-limiting, and guardrails for safe execution.

• Strong focus on reliability in agent workflows: idempotency, retries, fallbacks, circuit breakers, timeouts, and safe failure modes.

• Experience implementing observability for agents: logging of tool calls and reasoning traces, metrics, dashboards, and debugging workflows.

Soft Skills And Consulting Capabilities

• Strong communication skills with both technical and non-technical stakeholders; able to explain complex AI and architecture decisions in clear, accessible language.
• Comfort leading client workshops, running demos, and defending technical approaches with executives, product teams, and engineering teams.
• Ability to own a problem from discovery through implementation, balancing long-term architecture quality with the realities of client timelines and budgets.
• Collaborative mindset and willingness to mentor and uplevel other engineers and consultants on GenAI and agentic patterns.

Public Portfolio (Required)

• Public artifacts that demonstrate your work with GenAI and agents, such as:

• Open-source repositories (libraries, frameworks, or example applications involving LLMs/agents).

• Technical blog posts, talks, or walkthroughs explaining your LLM/agent system designs and trade-offs.

• Demos (live apps, recordings, or interactive playgrounds) that showcase real agent behavior and integrations.

• Ability to walk through these artifacts in detail during interviews: architecture, design choices, failure modes, and what you'd do differently now.

Nice-to-Have Qualifications

• Experience with data and AI platforms such as Databricks and Snowflake, including building or integrating GenAI/agent workflows on top of lakehouse architectures, feature stores, or governed data-sharing layers.
• Experience with enterprise SaaS ecosystems (e.g., Salesforce, ServiceNow, Microsoft 365, Google Workspace, ticketing or CRM systems) and embedding copilots/agents into those environments.
• Familiarity with security, compliance, and data governance constraints in enterprise contexts (PII handling, audit logs, RBAC, policy enforcement around model and data usage).
• Experience with evaluation frameworks and tooling for GenAI (prompt A/B testing, human-in-the-loop review flows, rubric-based evaluation, offline evaluation harnesses).
• Cloud certifications or AI-focused certifications (AWS, Azure, GCP) and/or prior work in consulting or professional services environments.
• Experience with machine learning beyond GenAI: designing and training predictive models (e.g., classification, regression, recommendation, time-series forecasting) and integrating them into production systems as part of larger solutions.
• Familiarity with common ML frameworks and tooling (e.g., scikit-learn, XGBoost, TensorFlow/PyTorch, MLflow, SageMaker), and an understanding of how predictive models and LLM/agent systems can complement each other in end-to-end architectures.

Interview Expectations

• Deep technical conversation about past GenAI and agentic projects, including architecture diagrams and trade-offs.
• Live or recorded walkthrough of your public artifacts (OSS, demos, or blog posts) with time for detailed questions.
• Practical design exercise focused on an agentic workflow (e.g., designing an agent that orchestrates several tools to complete a realistic business task, with attention to safety, reliability, and observability).

How You’ll Embody Our Core Values

At Plative, our core values shape how we work, collaborate, and grow. As part of the team, you will:

• Put People First by building trusted relationships with clients and mentoring teammates.
• Grow Together, Win Together by sharing knowledge, celebrating wins, and elevating others.
• Bring Your Authentic Self to Work by fostering openness, empathy, and integrity in every interaction.
• Take the Path You’ll Be Proud Of by delivering excellence, owning outcomes, and learning from challenges.
• Push Boundaries, Blow Minds by designing creative, scalable solutions that drive real impact.

What Happens Next?

We know that applying for a new role takes time and energy. At Plative, every application is thoughtfully reviewed by real people on our Talent Team. We aim to review applications within 2 weeks. If we think your skills align with what we’re looking for, we’ll be in touch to connect further!

Plative Inc. is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Plative is also committed to compliance with all fair employment practices regarding citizenship and immigration status.