Artificial Intelligence Architect

Role Summary

BlitzenX is looking for an

AI Architect

who can

build AI capabilities from zero to scale

. This role is not about experimentation or research for vanity metrics. This is about

designing, building, and shipping real AI products

that drive business outcomes.You will

define the AI vision

,

build and lead high-performance AI teams

, and

own the product roadmap from concept to production

. You will work closely with executive leadership, product managers, and engineering heads to turn AI strategy into deployed, revenue-impacting solutions.This role demands

technical authority, architectural depth, leadership maturity, and delivery discipline

.

Key Responsibilities

AI Architecture & Platform Ownership

Define and own the

end-to-end AI architecture

across data ingestion, model development, training, deployment, monitoring, and continuous improvement.Design

scalable, secure, and cost-efficient AI platforms

leveraging cloud, MLOps, and modern data architectures.Establish

reference architectures, design standards, and technical guardrails

for all AI initiatives.Ensure AI systems are

production-grade

, not experimental prototypes.

Product Roadmap – From Scratch to Delivery

Partner with business and product leaders to

identify AI use cases

aligned to revenue, efficiency, or customer impact.Translate ambiguous business problems into

clear AI product roadmaps

with milestones, risks, and measurable outcomes.

Own The Roadmap Across

Use-case discoveryData strategyModel selection and buildMVP definitionProduction rolloutIterative scaling and optimizationDrive

on-time, predictable delivery

of AI products with clear success metrics.

Team Building & Leadership

Build AI teams from the ground up

— data scientists, ML engineers, platform engineers, and AI product contributors.Hire for

execution strength, not academic theory

.Define team structure, roles, and ownership models that scale.Establish a

high-accountability, high-output culture

with clear performance expectations.Mentor senior engineers and architects to raise the overall technical bar.

Execution & Governance

Set up

AI development lifecycle processes

(MLOps, CI/CD, model governance, monitoring).

Define Standards For

Model versioningExplainabilityBias detectionSecurity and complianceAct as the final technical authority on AI decisions.Balance

speed with stability

—no uncontrolled experimentation in production.

Stakeholder & Executive Engagement

Communicate AI strategy, architecture, and progress clearly to

senior leadership and clients

.Influence decision-making with data, clarity, and technical credibility.Support pre-sales and solutioning efforts where AI is a differentiator.

Required Qualifications

10+ years of overall experience with

5+ years in AI/ML architecture or leadership roles

.Proven experience

building AI products from zero

—not inheriting mature systems.

Strong Hands-on Background In

Machine Learning & Deep LearningNLP, Computer Vision, or Predictive Modeling (at least one deeply)Deep expertise in

cloud platforms

(AWS / Azure / GCP) for AI workloads.Strong understanding of

MLOps frameworks

, model deployment, and monitoring.Experience leading and scaling

cross-functional AI teams

.Ability to make architectural decisions under ambiguity and pressure.

Technical Expectations

Solid programming background (Python mandatory).Experience with modern ML frameworks (TensorFlow, PyTorch, etc.).Strong data architecture fundamentals (data lakes, feature stores, pipelines).Familiarity with APIs, microservices, and production system integration.Clear understanding of

performance, cost optimization, and scalability trade-offs

.

What Success Looks Like

AI teams are built, stable, and delivering consistently.AI product roadmaps move from idea to production without chaos.Models are deployed, monitored, and improved—not abandoned.Leadership trusts your technical decisions.AI is no longer a buzzword inside BlitzenX—it is a

reliable product capability

.

Mindset Fit

Builder, not theorist.Comfortable with ownership and accountability.Execution-first mentality.High standards for engineering quality and delivery discipline.Thrives in a

performance-driven, employee-first culture

.

If You Want, Next I Can

Tighten this further for

LinkedIn posting

Customize it for

GenAI / LLM-focused architecture

Align it specifically to

client-facing AI platforms vs internal products

Convert it into a

BlitzenX hiring scorecard

Just tell me the direction.