Gramian Consultancy is looking for a GenAI Solution Architect / Presales Engineer to partner directly with customers and lead the end-to-end delivery of high-impact technical solutions. In this role, you will translate real-world challenges into production-ready systems leveraging Generative AI, Computer Vision, and Machine Learning. This position blends software engineering, ML engineering, architecture, and consulting.
What You'll Do
- Lead the backend and AI components of a new, HIPAA-compliant clinical intelligence platform in the urology domain.
- Architect, build, and deploy custom solutions leveraging GenAI, LLMs, Machine Learning and Vision models, and customer data sources.
- Lead full project lifecycles: scoping, solution design, development, implementation, testing, deployment, and iteration.
- Integrate and optimize AI/ML pipelines, including data preprocessing, prompt engineering, model selection, and evaluation.
- Build reliable, scalable software integrations using APIs, cloud services, and containerized systems.
- Troubleshoot complex technical issues across the stack—applications, models, data pipelines, infrastructure, and integrations.
- Act as the customer’s trusted technical advisor, enabling adoption of new product capabilities and AI features.
- Partner closely with internal product and engineering teams to communicate customer feedback and shape roadmap direction.
- Produce high-quality documentation, architecture diagrams, runbooks, and technical assets for customer teams.
- Mentor junior engineers and contribute to internal best practices for FDE delivery.
What We're Looking For
- 5–10+ years in engineering roles such as Forward Deployed Engineer, ML Engineer, Software Engineer, Solutions Engineer, Technical Consultant, or similar.
- Strong proficiency in Python, JavaScript/TypeScript, Go, or similar production-oriented languages.
- Hands-on experience with Machine Learning, including training, fine-tuning, evaluating, or deploying models.
- Direct experience with Generative AI (LLMs, multimodal models, vector databases, or RAG) and applying them to real-world problems.
- Exposure to Computer Vision techniques (detection, segmentation, OCR, embeddings, multimodal pipelines).
- Strong knowledge of ML frameworks (PyTorch, TensorFlow, OpenCV, etc.).
- Experience with cloud infrastructure (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
- Excellent communication skills with both technical and non-technical audiences.
- Comfort leading customer-facing engagements and guiding stakeholders through ambiguity.
- Willingness and ability to travel frequently.
- Prior experience in consulting, technical solutions, professional services, or customer-embedded technical roles.
Nice to Have
- Experience with vector databases, embedding pipelines, or retrieval-augmented generation (RAG).
- Experience building APIs, microservices, or distributed systems.
- Familiarity with MLOps tools (Docker, Kubernetes, model registries, CI/CD for ML).
- Background in deploying or fine-tuning CV models (YOLO, SAM, CLIP, DETR, etc.).
- Experience in startup or high-growth environments.
Technical Stack
- Languages: Python, JavaScript/TypeScript, Go
- ML Frameworks: PyTorch, TensorFlow, OpenCV
- Infrastructure: AWS, GCP, Azure, Docker, Kubernetes
Team & Environment
You will partner closely with internal product and engineering teams.
Work Mode
This is a global role, and candidates must be based in LATAM.




