Job Description

2025 marks the inflection point where AI evolved from productivity tool to autonomous teammate. Myridius is building AI-driven digital labor capabilities (AI-DLC) through our EVOQ platformtransforming how enterprises work. We need a visionary technical leader who can architect agentic AI solutions that don't just assist, but autonomously plan, execute, and deliver business outcomes.

You'll lead from the front: coding, consulting, and mentoring while driving our evolution from traditional IT services to AI-native solution delivery.

What You'll Do

1. Architect the Future: Agentic AI Led Engineering Innovation (40%)

Hands-On Engineering Leadership

Lead by example: Code, prototype, and architect using Python, LangChain, LlamaIndex, and agentic frameworks
Build autonomous agent systems using Ask-Plan-Agent patterns, multi-agent orchestration, and Model Context Protocol (MCP)
Develop Myridius EVOQ's AI-DLC capabilities: agents that independently break down projects, plan execution, self-correct, and deliver outcomes

Platform Development

Architect reusable AI frameworks and internal platforms that accelerate multi-client delivery
Stay ahead of the curve: Research and implement emerging capabilities (multi-agent systems, small language models, multimodal AI)
Drive market-differentiating innovationsolve unsolved industry problems, not just integrate APIs

Intellectual Property Creation

Identify and develop proprietary algorithms and architectural patterns within EVOQ
Lead patent filing efforts to establish defensible competitive advantages
Build IP moat that positions Myridius uniquely in the agentic AI space

2. Transform Client Businesses: Strategic Consulting (35%)

C-Level Advisory

Act as primary technical advisor to enterprise client executives
Translate complex business challenges into high-ROI AI solutions with clear transformation roadmaps
Guide clients through autonomous AI adoptionfrom pilot to production scale

Pre-Sales Excellence

Partner with sales teams to architect winning proposals and compelling PoCs
Demonstrate thought leadership through client-facing technical presentations
Define technical scope for multi-million dollar engagements

Production-Grade Delivery

Ensure all solutions meet enterprise standards: reliability, security, scalability, and governance
Architect MLOps pipelines and responsible AI frameworks that move beyond notebook code

3. Build World-Class Teams: Leadership & Mentorship (25%)

Talent Development

Build and mentor high-performing AI Engineering and Data Science teams
Foster culture of technical excellence, continuous learning, and innovation
Develop next-generation leaders who can architect autonomous AI systems

Quality & Standards

Establish best practices for agentic AI development, MLOps, CI/CD for AI
Conduct strategic code reviews focused on architecture, scalability, and maintainability
Implement responsible AI governance and ethical AI frameworks

What You Bring-

Core Technical Expertise- Enterprise & Cloud Architecture (Must-Have)

Enterprise Architecture: Deep understanding of microservices, service mesh, API gateway patterns, event-driven architectures
Full-Stack Development: Proficiency across frontend (React/Angular/Vue), backend (Python/Node.js/Java), and database layers
DevOps & Infrastructure: Hands-on experience with CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions), infrastructure as code (Terraform, CloudFormation)
Cloud Platforms: Production deployment experience on AWS, Azure, or GCP with deep knowledge of:
Compute: EC2, Lambda, App Service, Cloud Functions
Storage: S3, Blob Storage, Cloud Storage
Networking: VPC, load balancers, CDN
Security: IAM, Key Vault, Secret Manager, security best practices

Agentic AI & Autonomous Systems (Must-Have)

Deep understanding of autonomous agent architectures (Ask-Plan-Agent, ReAct, multi-agent systems)
Experience with orchestration frameworks: LangChain, LlamaIndex, DSPy, AutoGen
Hands-on with multi-agent orchestration platforms: n8n, Make (Integromat), Apache Airflow, or Prefect
Familiarity with Model Context Protocol (MCP), agent memory systems, and tool integration

Generative AI Mastery

Production experience with LLMs: OpenAI GPT-4, Anthropic Claude, Llama 3, Mistral
Advanced prompt engineering, Retrieval-Augmented Generation (RAG) architectures
Fine-tuning expertise: PEFT, LoRA, instruction tuning

ML/AI Foundation

Expert-level Python, PyTorch/TensorFlow, Scikit-learn
Strong understanding of transformer architectures, embeddings, and vector operations

Data & Infrastructure

Hands-on with Vector Databases: Pinecone, Milvus, Weaviate, Qdrant
SQL/NoSQL database design for AI applications (PostgreSQL, MongoDB, Redis)
Cloud AI platforms: AWS (Bedrock/SageMaker), Azure (OpenAI Service), GCP (Vertex AI)

MLOps & Production AI

Production ML pipelines: MLflow, Kubeflow, or equivalent
Containerization: Docker, Kubernetes for AI workloads
CI/CD for machine learning systems
Monitoring & observability: Prometheus, Grafana, CloudWatch

Experience Requirements

18-22 years in software engineering, architecture, or consulting
Minimum 2+ years of dedicated, hands-on AI/ML work (not just managing AI teams)
Proven track record deploying AI solutions to production at enterprise scale
Experience with autonomous agent systems or multi-step AI workflows (strong plus)

Strategic Impact

Led technical teams (10+ engineers) in complex, multi-year programs
Consulted with C-level stakeholders on technology transformation
Contributed to patents, published research, or notable open-source projects (preferred)

Communication Excellence

Exceptional ability to explain complex AI concepts to business leaders
Comfortable presenting to boards and executive committees
Can translate technical capabilities into business value narratives

Education

Bachelor's or Master's degree in Computer Science, AI, Mathematics, or related field
PhD in AI/ML (plus, but not required)

Why Should You Apply

Ride the inflection point: Join at Q4 2025's agentic AI breakthroughthe once-in-a-decade moment when AI transforms from tool to autonomous teammate. Shape the market while it's being defined.
Build something meaningful: Own EVOQ platform's technical evolution and create defensible IP through patents. This isn't maintenanceit's greenfield innovation with enterprise resources.
Strategic influence at scale: Direct board-level exposure through reporting to Head of Solutions & Strategy. Guide multi-million dollar client transformations, not just implement requirements.
Technical freedom + business impact: Lead from the front with hands-on coding while architecting solutions that redefine IT services delivery. No pure management trapyou'll build, mentor, and shape strategy.

Cultural Fit

You thrive in environments that value:

Forward-thinking with pragmatic executionahead of market but with clear path to value
Straight-shooting communicationno corporate speak, direct and actionable
Continuous learningAI is evolving weekly; curiosity is non-negotiable
Outcome obsessiontechnology for business impact, not technology for its own sake

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