Solutions Engineer

Solutions Engineer (Full-Time, On-Site in Lahore)

Cutting-Edge Integrations:
Shape how enterprises and developers interact with the AI Protocol—the infrastructure powering dApps like , , and You'll be hands-on with APIs, SDKs, and GPU-backed AI services, delivering integrations and reference implementations that make adoption seamless.

Global Impact:
Work directly with partners, customers, and enterprise teams across the world. Backed by tier-one investors like Binance, Galaxy Interactive, Winklevoss Capital, , Polygon, Multicoin Capital, and Mark Cuban, your work will not only scale across industries but also set benchmarks for how AI and blockchain connect in production.

Future-Proof Architecture:
Build solutions at the intersection of AI and decentralized infrastructure. From LLM/CV/audio inference pipelines to secure, scalable integrations across cloud-native stacks, you'll design and deliver the kind of architecture that defines the next decade of AI adoption.

What you'll do

• Architect & deliver
  customer integrations across our APIs, webhooks, and SDKs; build POCs and reference apps in Python and JavaScript/TypeScript.
• Debug across the stack:
  auth (OAuth2/JWT), REST/gRPC calls, webhooks, queues/streams, storage (S3), GPU inference services, containers, and CI/CD.
• Create developer resources:
  sample repos, notebooks, Postman collections, quickstarts, and implementation guides; run technical workshops and office hours.
• Productionize POCs:
  harden for scale (idempotency, retries, back-pressure), add telemetry, and define SLOs/SLA handoffs with SRE/Infra.
• Security by default:
  secrets/key management, least-privilege IAM, data minimization, and compliance-friendly design (PII boundaries, data residency knobs).
• Close the loop with Product & Eng:
  surface patterns, spec changes, and quality signals; file actionable tickets/PRs rather than just reports.
• Pre- and post-sales support:
  scope solution designs, estimate effort, de-risk unknowns with spikes, then hand over to Customer Success with crisp runbooks.

Minimum qualifications

• 3+ years in Solutions Engineering, Developer Success, Systems/Backend Engineering, or similar.
• Strong
  Python
  plus one of
  
  ; fluency with HTTP, REST, JSON, retries, pagination, and webhook patterns.
• Experience building or integrating
  AI/ML pipelines
  (e.g., PyTorch) or
  video/audio processing
  (ffmpeg, streaming, job orchestration).
• Cloud & DevOps:
  AWS
  (EC2/EKS/ECR/S3/CloudWatch),
  Docker/Kubernetes
  ,
  CI/CD
  (GitHub Actions/GitLab CI), and
  IaC
  (Terraform).
• Datastores & messaging:
  PostgreSQL
  ,
  Redis
  , and one queue/stream (
  Kafka
  ,
  RabbitMQ
  , or
  Redis Streams
  ).
• Vector search/RAG
  (FAISS, Weaviate, or Pinecone) and prompt/tooling patterns for LLM-based agents
• Observability: logs, metrics, traces (e.g., OpenTelemetry + ELK/Prometheus/Grafana); can turn debugging into repeatable runbooks.
• Customer-facing communication: can translate deep technical issues into clear options, trade-offs, and decisions.

Nice to have

• Web3
  experience (EVM/Solidity or Solana/Rust), wallet flows, signatures, and event indexing.
• GPU inference
  (Triton, TensorRT) and workload scheduling (Runpod/AWS); cost and latency tuning.
• SSO/OIDC/SAML
  , SCIM, and enterprise security reviews.
• Frontend familiarity (React) for internal tools and lightweight partner demos

Remuneration:
Competitive; remittance-based model, with role-aligned incentives and growth opportunities.

If you're ready to make an impact in the AI space, we'd love to hear from you. Apply by sending your CV to

or feel free to reach out directly to discuss this opportunity. Know someone who might be a fit? Please share this post with them