In an industry full of AI hype,
prove what you can actually build.
Resumes and self-claimed titles can’t distinguish between someone who played with a chatbot and an engineer who can architect, evaluate, and maintain production AI under strict latency, cost, and reliability bounds. Abhyaas validates actual competence across Beginner, Pro, and Expert levels.
The Proof Gap in Modern Engineering
Why professional certification is critical right now
The barrier to writing code has collapsed, but the barrier to delivering reliable, safe, and cost-effective systems in production has never been higher.
Resumes cannot verify AI competence
Every candidate claims “Prompt Engineering” and “LLM Application Development.” Hiring teams and clients are inundated with noise. An Abhyaas credential provides audited proof that you understand the physics of non-deterministic systems: token economics, offline eval suites, and guardrails at the boundary.
No leaked dumps, zero trivia memorization
Traditional certifications test multiple-choice trivia easily memorized from dump sites. Abhyaas exams test architectural decision-making: diagnosing silent retrieval degradation, choosing chunking strategies, mitigating context pollution, and handling provider outages with graceful fallback.
Diagnostic gap analysis on every attempt
Whether you pass or fail, you receive a granular domain-by-domain breakdown. If your retrieval grounding is 58% while your prompt design is 85%, Abhyaas maps your exact weak domains to specific chapters in authoritative engineering texts, transforming the exam into an actionable learning engine.
Unforgeable employer verification
Every issued certificate is stamped with a non-sequential identifier and backed by a live public verification URL. Employers, recruiters, and clients can instantly verify credential validity, issue date, and certified competence tier directly from the server.
Structured Career Progression
Three exam phases for every role
Capability is not a binary switch. Each of our 32 roles offers three distinct certification rungs, giving engineers an unambiguous benchmark for career advancement.
Beginner / Foundation
Validates core principles, ecosystem toolchains, safe retrieval basics, clean prompting, and the ability to construct features without constant supervision.
- ✓ 50 dynamically sampled questions
- ✓ 75 minutes exam duration
- ✓ 70% passing cut score
- ✓ 3 attempts included (1 exam + 2 retakes)
Pro / Professional
Validates production ownership: automated evaluation suites, schema enforcement, latency and cost bounds, guardrail policies, telemetry, and handling incident degradation states.
- ✓ 60 complex scenario questions
- ✓ 90 minutes exam duration
- ✓ 70% passing cut score
- ✓ 3 attempts included (1 exam + 2 retakes)
Expert / Specialist
Validates technical authority: multi-agent coordination, zero-downtime provider migrations, enterprise governance, novel failure forensics, and organizational architecture.
- ✓ 70 advanced architectural questions
- ✓ 105 minutes exam duration
- ✓ 75% higher pass threshold
- ✓ 3 attempts included (1 exam + 2 retakes)
Live Exam Catalog
Select your role & certificate phase
Browse all 32 specialized engineering disciplines across Beginner ($99), Pro ($199), and Expert ($349) tiers to inspect what each exam measures and begin your evaluation.
AI Application Engineering & Agentic Systems
32 ROLESForward-Deployed Engineer
Certifies judgement in deploying and owning systems inside customer environments.
ML / AI Systems & Modeling
32 ROLESAI Evaluation Engineer
Designs the measurement: what counts as correct, how it is judged, and why the benchmark can be trusted.
Security, Safety & Governance
32 ROLESAI Governance Specialist
Makes AI use defensible: inventory, risk classification, documented controls and evidence a regulator would accept.
AI Infrastructure, Platforms & Operations
32 ROLESAI Infrastructure Engineer
Designs and operates the infrastructure AI workloads run on, from accelerator choice to inference topology.
AI Infrastructure, Platforms & Operations
32 ROLESAI Performance Engineer
Finds where the time and the money actually go, and proves the optimisation worked.
Architecture, Product & Leadership
32 ROLESAI Product Manager
Decides what an AI product should do, what quality bar it must clear, and what it must refuse to do.
AI Infrastructure, Platforms & Operations
32 ROLESAI Reliability Engineer
Defines what 'working' means for a non-deterministic system, measures it, and runs the incident when it stops.
ML / AI Systems & Modeling
32 ROLESAI Research Engineer
Builds the systems research runs on: training infrastructure, reproducibility, scaling and experiment tooling.
Security, Safety & Governance
32 ROLESAI Safety Engineer
Works on the harms a correctly functioning system can still cause, and on the controls that reduce them.
Security, Safety & Governance
32 ROLESAI Security Engineer
Models the attack surface of AI systems and chooses mitigations that survive contact with a real adversary.
Architecture, Product & Leadership
32 ROLESAI Solutions Architect
Architects AI-bearing systems: where the model sits, what it is allowed to do, and what happens when it is wrong.
AI Application Engineering & Agentic Systems
32 ROLESAgentic Workflow Engineer
Designs multi-step agent systems: tool use, planning, state, recovery and the limits of autonomy.
Data Engineering & Modern Data Stack
32 ROLESAnalytics Engineer
Turns raw tables into a modelled, tested, documented layer the business can query without asking anyone.
AI Application Engineering & Agentic Systems
32 ROLESApplied AI Engineer
Applies existing models to concrete business problems end to end, choosing when not to use a model at all.
ML / AI Systems & Modeling
32 ROLESApplied Scientist
Turns an open research question into a measurable, shippable result, and knows when the result does not hold.
AI Infrastructure, Platforms & Operations
32 ROLESCloud AI Engineer
Delivers AI workloads on managed cloud services, and owns the identity, network and cost consequences.
ML / AI Systems & Modeling
32 ROLESComputer Vision Engineer
Builds systems that interpret images and video, and knows how they fail on data the camera actually produces.
Data Engineering & Modern Data Stack
32 ROLESData Architect
Decides how an organisation's data is shaped, owned, governed and allowed to move.
Data Engineering & Modern Data Stack
32 ROLESData Engineer
Moves data reliably and makes it trustworthy at the point of use.
Data Engineering & Modern Data Stack
32 ROLESData Platform Engineer
Operates the shared data platform: ingestion, compute, catalogue, access and the cost of all of it.
Data Engineering & Modern Data Stack
32 ROLESData Scientist
Answers a business question with data honestly, including when the data cannot answer it.
Architecture, Product & Leadership
32 ROLESEnterprise Architect
Works at the level of capabilities, standards and multi-year sequencing rather than individual systems.
AI Infrastructure, Platforms & Operations
32 ROLESML Infrastructure Engineer
Runs the compute, storage and network layer that training and inference actually consume.
AI Infrastructure, Platforms & Operations
32 ROLESML Platform Engineer
Builds the internal platform other ML teams build on, and is judged on their throughput rather than their code.
AI Infrastructure, Platforms & Operations
32 ROLESMLOps Engineer
Owns the path from a trained model to a served one, and everything that keeps it serving correctly.
ML / AI Systems & Modeling
32 ROLESMachine Learning Engineer
Builds, trains, validates and ships models, and owns their behaviour once real data reaches them.
ML / AI Systems & Modeling
32 ROLESNLP Engineer
Works on language tasks end to end, including the many that should not be solved with a large model.
Architecture, Product & Leadership
32 ROLESSoftware Architect
Owns the structure of a system: its boundaries, its failure behaviour, and the decisions that are expensive to reverse.
Architecture, Product & Leadership
32 ROLESSolutions Architect
Designs a solution against real constraints and defends the trade-off to the people who have to live with it.
Architecture, Product & Leadership
32 ROLESTechnical Lead
Is accountable for a team's technical output: sequencing, quality, review, and the decisions nobody else will make.
AI Application Engineering & Agentic Systems
32 ROLESAI Application Engineer
Validates the ability to design, ground, evaluate and operate an application built on a language model.
AI Application Engineering & Agentic Systems
32 ROLESLLM Engineer
Selects, adapts, serves and evaluates language models, and reasons about behaviour that changes between identical calls.
Enterprise & Engineering Teams
Hiring or benchmarking technical teams?
Engineering leaders use Abhyaas to audit talent objectively, eliminate resume ambiguity, and guarantee that every engineer building production software meets verified capability thresholds.
Ready to stand out with verified proof of competence?
One-time payment with every retake included. Choose your role, study the blueprint, and earn a verifiable credential employers trust.