Deploying Production
Enterprise AI & Distributed Systems
Iām Muhammad Sayyam Saleem, a Forward Deployed Engineer who embeds directly with enterprise teams to design, optimize, and scale mission-critical RAG pipelines, autonomous agent swarms, and high-throughput streaming architectures.
vLLM AWQ 4-bit optimization & TensorRT-LLM server tuning.
Air-gapped Kubernetes & redundant fallback agent loops.
ClickHouse + Kafka distributed telemetry stream processing.
API token cost reduction & cloud infrastructure efficiency.
Production-Grade RAG &
Enterprise Agent Infrastructure
Click on any architectural component below to inspect real-time data flow, latency targets, and code snippets deployed in enterprise environments.
Autonomous Multi-Agent Router (MCP)
Dynamic task decomposition router invoking specialized tools (SQL Generator, Document Analyzer, Python Sandbox) via standard MCP protocols with automatic loop termination.
@agent_router.tool(name="execute_sql_analytics")
async def run_query(ctx: AgentContext, query: str) -> QueryResult:
sanitized = sql_guardrail.sanitize(query)
return await db.fetch_all(sanitized)High-Impact Enterprise
Field Deployments & Outcomes
Real enterprise case studies demonstrating how Forward Deployed Engineering solves complex data bottlenecks, slashes latency, and drives measurable business value.
Enterprise Multi-Agent RAG & Knowledge Graph Engine
Reduced doc search latency from 4.5s to 24ms across 10M+ financial records.
The Challenge
Financial analysts spent over 3 hours daily querying fragmented document repositories. External cloud APIs violated strict data privacy regulations, while existing semantic search pipelines had unacceptable 4.5s latency.
FDE Engineering Solution
Forward-deployed on-premises to build a hybrid vector retrieval pipeline (Qdrant + BM25 sparse re-ranking) powered by AWQ-quantized Llama 3 models served via vLLM with custom MCP agent routers.
Key Engineering Outcomes & ROI:
Calculate Enterprise
ROI & Latency Optimization
See how forward deployed engineering optimizations (vLLM quantization, prompt caching, hybrid vector indexing) reduce cloud infrastructure costs and cut model latency.
Your Current Infrastructure Metrics
($14,700 saved every month with zero loss in output quality)
Comprehensive FDE
Skill & Technology Graph
Battle-tested technologies and architectural methodologies utilized to deploy enterprise AI systems on-premise and in cloud environments.
Enterprise AI & Model Serving
PRODUCTION STACKAWQ 4-bit quantization, PagedAttention VRAM tuning
Dense/Sparse hybrid search, Qdrant, Pinecone, BM25
Autonomous agent swarms, Model Context Protocol standard
Guardrails AI, Presidio PII sanitization filters
Backend & Systems Engineering
PRODUCTION STACKFastAPI, Asyncio, Pydantic, high-throughput microservices
Strict TypeScript, React Server Components, Tailwind CSS
JWT, Bcrypt, mTLS, Role-Based Access Control (RBAC)
High-performance contract-driven API endpoints
Databases & Streaming Pipelines
PRODUCTION STACKUUIDv7 PKs, GIN index optimization, asyncpg, Alembic
Real-time streaming ingestion, windowed analytics
High-volume telemetry analytics & log compression
Milvus, Qdrant, Pinecone, HNSW index tuning
Cloud Infra & Forward Deployment
PRODUCTION STACKPrivate enterprise VPCs, Helm charts, Docker containers
Multi-node H100/A100 GPU cluster management
Real-time telemetry, SLA alerting, latency profiling
Embedding with client eng teams, rapid prototyping
Forward Deployment
Mission History & Impact
Track record of embedding with high-growth startups and enterprise clients to solve mission-critical engineering challenges.
Lead Forward Deployed Engineer
Senior Systems & Data Engineer
Forward Deployed AI Solutions Engineer
Trusted by Engineering Leaders
"Sayyam embedded with our core infrastructure team and within 3 weeks completely redesigned our vector search pipeline. Our P99 latency dropped from 3.2s to 28ms while maintaining HIPAA compliance."
"Finding an engineer who can sit across from executive stakeholders to translate business goals into air-gapped GPU clusters is rare. Sayyam is the pinnacle of Forward Deployed Engineering."
"Sayyam's vLLM quantization work saved us over $100k a month in OpenAI API costs. His autonomous multi-agent routing standard is now our company baseline."