Select your current position

Pick a role and level — we'll show the growth path, skills and gap analysis.

Development path

Junior

0-2 years

Current

Responsibility: Выполнение задач под руководством старших коллег. Изучение кодовой базы, стандартов и процессов команды. Написание кода по спецификациям, исправление простых багов, написание тестов.

Key skills:

ChatGPT / Claude Need
LLM Fine-tuning Need
Prompt Engineering for Code Need
Vector Databases Need
LLM Evaluation Need

Middle

2-5 years

Next

Responsibility: Самостоятельная разработка фич от декомпозиции до деплоя. Участие в code review. Оптимизация производительности. Менторинг junior-разработчиков. Участие в архитектурных обсуждениях.

Key skills:

ChatGPT / Claude Need
LLM Fine-tuning Need
Prompt Engineering for Code Need
Vector Databases Need
LLM Evaluation Need

Senior

5-8 years

Responsibility: Проектирование архитектуры компонентов и сервисов. Решение сложных технических проблем. Ведение технического долга. Code review как gatekeeper качества. Менторинг middle-разработчиков. Выбор технологий для новых задач.

Key skills:

AI Agent Frameworks Need
AI Agents for Development Need
AWS Need
ChatGPT / Claude Need
Elasticsearch / OpenSearch Need
gRPC & Protocol Buffers Need
Kubernetes Core Need
LLM Fine-tuning Need
LLM Applications Need
MLflow Need
Model Context Protocol (MCP) Need
Model Serving Need
Pandas / Polars Need
PostgreSQL Need
Prompt Engineering for Code Need
Python Web Frameworks Need
PyTorch Need
RAG Architecture Need
Redis Need
REST API Design Need
S3 / Object Storage Need
Server-Sent Events & Streaming Need
Task Queues Need
Transformers & NLP Need
Unit Testing Need
Async Programming Need
Vector Databases Need
Model Monitoring Need
LLM Evaluation Need
OOP & SOLID Principles Need
Experiment Tracking Need

Lead / Staff

7-12 years

Responsibility: Техническое лидерство команды или направления. Проектирование системной архитектуры. Координация с другими командами. Формирование стандартов и best practices. Участие в найме. Планирование технического roadmap.

Key skills:

AI Agent Frameworks Need
AI Agents for Development Need
AWS Need
ChatGPT / Claude Need
Elasticsearch / OpenSearch Need
gRPC & Protocol Buffers Need
Kubernetes Core Need
LLM Fine-tuning Need
LLM Applications Need
MLflow Need
Model Context Protocol (MCP) Need
Model Serving Need
Pandas / Polars Need
PostgreSQL Need
Prompt Engineering for Code Need
Python Web Frameworks Need
PyTorch Need
RAG Architecture Need
Redis Need
REST API Design Need
S3 / Object Storage Need
Server-Sent Events & Streaming Need
Task Queues Need
Transformers & NLP Need
Unit Testing Need
Async Programming Need
Vector Databases Need
Model Monitoring Need
LLM Evaluation Need
OOP & SOLID Principles Need
Experiment Tracking Need

Principal

10+ years

Responsibility: Техническая стратегия на уровне компании или домена. Кросс-организационное влияние. Решение системных проблем бизнеса через технологии. Менторинг lead-инженеров. Публичное представление компании.

Key skills:

AI Agent Frameworks Need
AI Agents for Development Need
AWS Need
ChatGPT / Claude Need
Elasticsearch / OpenSearch Need
gRPC & Protocol Buffers Need
Kubernetes Core Need
LLM Fine-tuning Need
LLM Applications Need
MLflow Need
Model Context Protocol (MCP) Need
Model Serving Need
Pandas / Polars Need
PostgreSQL Need
Prompt Engineering for Code Need
Python Web Frameworks Need
PyTorch Need
RAG Architecture Need
Redis Need
REST API Design Need
S3 / Object Storage Need
Server-Sent Events & Streaming Need
Task Queues Need
Transformers & NLP Need
Unit Testing Need
Async Programming Need
Vector Databases Need
Model Monitoring Need
LLM Evaluation Need
OOP & SOLID Principles Need
Experiment Tracking Need

Gap analysis: skills to develop

To reach the next level you'll need to develop:

ChatGPT / Claude

Independently integrates ChatGPT and Claude API into production pipelines. Configures system prompts, function calling, and streaming responses. Compares models by quality and cost for specific tasks.

LLM Fine-tuning

Independently conducts LLM fine-tuning: LoRA/QLoRA, instruction dataset preparation, hyperparameter tuning. Monitors training via W&B, evaluates results on held-out datasets.

Prompt Engineering for Code

Independently develops production-ready prompts: structured output parsing, error recovery prompts, multi-turn dialog management. Applies systematic approach to prompt design and testing.

Vector Databases

Independently administers vector databases in production: Pinecone, Weaviate, Qdrant. Configures indexes (HNSW, IVF), optimizes recall vs latency, manages collections and metadata.

LLM Evaluation

Independently designs evaluation pipelines: custom benchmarks, domain-specific eval sets, human evaluation protocols. Compares models across multiple metrics for production decision-making.