Build the sovereign alternative.
Are you ready to embark on a very different kind of adventure? Rindogatan is here to challenge the very notion of consultancy services by empowering our customers beyond the imaginable.
Forward-deployed, by design.
Replacing legacy workflows and tools with agentic loops and ad hoc products demands an entirely new approach to change management and technical literacy. Are you ready to join us on the journey?
Delivery, forward-deployed
Client-embedded engineers and leads who scope, build, and ship AI workflows into a single client's production environment. The billable core, and the people who decide whether the work actually lands.
Forward-Deployed AI Engineer
Our flagship client-embedded role: scope, build, and ship AI workflows end-to-end inside one client's production environment, then feed what you learn back into how we work.
- →Embed with an enterprise client and own discovery → design → build → production rollout
- →Build RAG pipelines, agents, and evals against the client's real data and constraints
- →Make the frontier-vs-sovereign call workload by workload, and stand up the sovereign path
Sector Solutions Lead
A senior forward-deployed engineer who owns one industry's playbook and account outcomes, translating a sector's hardest problems into shipped AI solutions.
- →Own the AI solution architecture and outcomes for one vertical (e.g. banking, healthcare)
- →Carry the sector's regulatory map (DORA, Annex III, EHDS…) into every design
- →Mentor forward-deployed engineers and grow the account
Agent Architect
Design the multi-agent and agentic-workflow systems, orchestration, tool use, memory, guardrails, that automate a client's marketing, HR, or finance back office.
- →Architect agent orchestration, tool use, and human-in-the-loop checkpoints
- →Build guardrails, logging, and evals so autonomy stays auditable
- →Productise repeatable agent patterns across engagements
Platform, sovereign infrastructure
The people who make self-hosted, open-weight inference real on European soil, the moat that separates us from a frontier-API reseller.
Sovereign Inference Engineer
Stand up and operate self-hosted open-weight model serving on EU, on-prem, or private-cloud infrastructure. This role is the moat.
- →Run open-weight serving (vLLM / SGLang) on Kubernetes with the right GPUs
- →Size, quantize, and fine-tune models for cost, latency, and quality
- →Own data-residency architecture so inference never leaves the perimeter
LLMOps / Eval Platform Engineer
Build the firm's reusable evaluation, monitoring, and CI/CD-gating platform for model and agent quality, drift, cost, and guardrails, so we ship with evidence.
- →Build eval suites and CI gates for model and agent quality
- →Monitor drift, bias, cost, and latency in production
- →Turn evaluation into a repeatable platform across all delivery
Data Platform & Privacy Engineer
Engineer the sovereign data foundation, pipelines, residency controls, encryption, pseudonymisation, access governance, so personal data never leaves the EU perimeter.
- →Build EU-resident pipelines with privacy-by-design and full lineage
- →Implement pseudonymisation, encryption, and access governance
- →Make data-minimization a default, not an afterthought
Governance, advisory
The EU AI Act and GDPR turned into a service: risk classification, conformity, outsourced DPO, and the frontier-vs-sovereign decision, sold as advisory.
AI Governance & EU AI Act Specialist
“AI Officer-as-a-service”: map AI-system risk across the lifecycle, run conformity and documentation against the EU AI Act, and operate our frontier-vs-sovereign framework for clients.
- →Classify AI systems by risk tier and run conformity / documentation
- →Operate the frontier-vs-sovereign placement framework with clients
- →Liaise with auditors and regulators; build the governance operating model
DPO / Data-Protection Counsel
Outsourced DPO and GDPR-meets-AI-Act advisory: DPIAs, legal basis for AI processing, automated-decision transparency, and worker-information rights.
- →Act as outsourced DPO and run DPIAs for AI processing
- →Advise on legal basis, Art. 22 automated decisions, and transparency
- →Bridge GDPR and the AI Act for HR, Legal, and regulated industries
Databricks, on the lakehouse
The specialists who roll out the Databricks stack for clients and take it further with sovereign AI: pipelines, models and agents, governance, analytics, and platform operations. Our newest track, growing with the partnership.
Databricks Data Engineer
Build scalable, resilient pipelines on the lakehouse: Medallion (Bronze, Silver, Gold) architectures and large-scale ingestion and transformation, engineered for AI to consume and for a DPO to audit.
- →Design Medallion pipelines and optimise large-scale ingestion and transformation on Delta Lake
- →Build declarative ETL with Delta Live Tables (Lakeflow) and distributed processing on Apache Spark
- →Orchestrate complex jobs with Databricks Workflows, wired for lineage and audit
Databricks AI & ML Engineer
Design, train, and deploy predictive models and agentic GenAI on Databricks, and own the end-to-end MLOps lifecycle, with the decisioning kept on infrastructure the client controls.
- →Build and tune AI agents with Mosaic AI and Agent Bricks, and ship RAG on Vector Search
- →Track, deploy, and monitor models with managed MLflow across the MLOps lifecycle
- →Govern enterprise LLM interactions through the Unity AI Gateway
Databricks Lakehouse Architect
Design cost-efficient lakehouse topologies, enterprise-wide governance, and secure multi-cloud or hybrid strategies, with the sovereignty line drawn into the architecture from the start.
- →Design platform topology and Lakehouse patterns for cost, scale, and resilience
- →Establish enterprise governance and access control with Unity Catalog
- →Guide serverless compute and secure cross-org exchange with Delta Sharing across multi-cloud and hybrid
Databricks Analytics Engineer
Bridge raw data and the business: model curated datasets, tune query performance, and serve interactive dashboards and natural-language exploration straight to stakeholders.
- →Model curated datasets and serve dashboards on Databricks SQL, the serverless warehouse
- →Optimise query performance with the Photon engine and Materialized Views
- →Open natural-language data exploration with AI/BI and Databricks Genie
Databricks Platform Administrator
Secure and run the platform: workspace security, infrastructure as code, network topology, and monitoring of compute cost and platform health across the estate.
- →Automate workspace and infrastructure deployment with Terraform for Databricks
- →Configure RBAC, ABAC, and data lineage in Unity Catalog, and harden workspace security profiles
- →Monitor spend and platform health with system tables for granular billing and usage
Real production work, not slideware.
You ship AI into a client's production environment and own the outcome. The feedback loop is days, not quarters.
A sovereign stack worth mastering.
Self-hosted open-weight models on European infrastructure, the scarce, future-proof skillset, not another wrapper around a public API.
Governance as a first-class craft.
The EU AI Act made AI governance a profession. Here it is core delivery, not a compliance afterthought.
European, humane, and honest.
We build AI that respects the people whose data it touches, and we tell clients the truth, including when the answer is “don't.”
Don't see your
exact role?
We are building the team that proves Europe can deliver enterprise AI on its own terms. Tell us who you are and what you'd want to own. Rindogatan reads every introduction.