Forward Deployed Engineer (FDE)

About Indicium AI

Indicium AI is trusted by the world's leading enterprises to deliver AI into production at scale. We are a global, AI-native consultancy with deep expertise across Financial Services, Energy & Utilities, Healthcare & Life Sciences, Retail & CPG, and Manufacturing - guiding organizations from strategy through build to measurable business outcomes. With 600+ AI experts, 50+ enterprise clients, and five global locations, we work side-by-side with the world's leading AI partners - including Anthropic, Databricks, AWS, OpenAI, and Microsoft - to deliver modern AI with speed, clarity, and lasting impact.

As a global company, we offer career opportunities across Europe and the Americas and are looking for talent eager to grow globally with our team. Please indicate in your application if you are available to work abroad and if you hold a European passport.

---

About the Opportunity

The Senior Forward Deployed Engineer is the primary technical and advisory reference at the client. Responsible for leading highly complex data and AI projects from end to end, acting autonomously or coordinating internal and client teams. Possesses a strategic vision of the business problem, multidisciplinary technical depth, and the ability to influence high-level decisions. Serves as a technical ambassador for Indicium, ensuring the quality, value, and expansion of delivered projects.

Their role combines technical depth in AI Engineering — LLMs, RAG, agents, MLOps — with a consultative vision and the ability to operate directly within the client's environment. They seamlessly navigate all data disciplines, with generative and agentic AI serving as their primary vector for value delivery.

Key Responsibilities

• Lead complex end-to-end data and AI projects at the client: diagnostics, architecture, implementation, delivery, and knowledge transfer;

• Define the technical and architectural approach for data and AI solutions, considering business, technology, and operational constraints of the client;

• Act as a senior technical consultant alongside client leadership — from technical ICs to C-level —, influencing strategic decisions, managing stakeholder conflicts, and building long-term relationships of trust;

• Coordinate internal DE, AE, DS, and AI Engineering teams allocated to the project, ensuring alignment, quality, and on-time delivery;

• Lead the architecture and implementation of generative and agentic AI solutions at the client — LLMs, RAG, multi-agent systems, fine-tuning, and model evaluation —, defining when and how each approach applies to the context and constraints of the environment;

• Develop and deploy MCP servers and integrations with tool ecosystems that extend agent capabilities within the client's enterprise infrastructure;

• Evaluate, select, and integrate AI providers and tools (OpenAI, Anthropic Claude, Google Gemini, Amazon Bedrock, etc.) considering cost, latency, security, and regulatory compliance within the client's context;

• Identify, structure, and present project expansion opportunities and new use cases to the client and the commercial team;

• Ensure governance, security, and compliance of data and AI solutions delivered within the client's environment;

• Establish MLOps practices within the client's environment: model versioning, drift monitoring, evaluation pipelines, experiment tracking, and secure production deployment;

• Mentor Junior and Mid-level FDEs, fostering the technical and consultative growth of the team;

• Lead the technical management of the project at the client: define scope, milestones, success metrics, and ensure results are measurable and clearly communicated to all parties;

• Lead the building of reusable accelerators, frameworks, and methodologies that scale the impact of the FDE practice across accounts; contribute technical feedback to Indicium's internal solutions and product roadmap;

• Act as an internal reference for highly complex data and AI projects, supporting other teams when necessary.

Preferred Qualifications & Experience

• Consolidated experience in data and AI projects, with a track record in at least three disciplines: Data Engineering, Analytics Engineering, Data Science, and/or AI Engineering;

• Proven experience working directly with clients in a consultative or technical implementation context;

• Advanced mastery of SQL, Python, and Modern Data Stack tools (dbt, Airflow, Spark, BI platforms, etc.), with experience in AI Engineering frameworks and libraries;

• Advanced experience with LLMs, RAG, agent development, and fine-tuning — including model evaluation, AI system observability, and risk mitigation such as prompt injection and hallucination;

• Advanced experience with cloud services (AWS, GCP, or Azure) and data infrastructure;

• Experience in technical leadership of multidisciplinary teams, with the ability to guide AI Engineers, Data Engineers, and Analytics Engineers in building integrated AI solutions;

• Executive communication skills: ability to present complex technical solutions to C-level and business leadership;

• High autonomy: capable of operating without a defined scope, identifying problems before the client articulates them, making decisions, and delivering to production;

• Strategic business vision combined with technical depth;

• Advanced/fluent English.

Nice to haves

• Knowledge of the Financial Services Industry (FSI) — including regulatory dynamics, risk structures, compliance requirements, and operational standards of financial institutions — with the ability to apply it directly to the design and validation of data and AI solutions;

• Experience in technology or data consulting firms;

• Technical certification in a public cloud platform (AWS, Azure, GCP) at the Professional/Specialty level or equivalent;

• Anthropic Claude Certified Architect — Foundations (CCA-F) certification or equivalent;

• Experience with multi-agent architectures and large-scale production AI applications;

• Experience with data and AI security and governance (LGPD, GDPR, prompt injection, guardrails);

• Experience with systematic large language model evaluation (LLM evals), benchmarks, and testing frameworks such as RAGAS, PromptFlow, or equivalents;

• Experience with Databricks, Snowflake, or enterprise data platforms;

• Knowledge of project management methodologies (PMBOK, Scrum, etc.);

• Contributions to open-source projects in AI Engineering or technical publications on production-grade AI applications;

• Postgraduate degree in Computer Science, Data Engineering, Artificial Intelligence, or related fields.

---

Why Indicium AI

• Work on AI projects that actually transform the world's largest enterprises

• Use cutting-edge AI tools and technologies every single day

• Collaborate with global teams on high-impact, real-world solutions

• Be backed by a supportive team that's genuinely in your corner

• Benefit from serious investment in your learning and career growth

• Earn competitive compensation and benefits

• Enjoy company events and gatherings that bring the global team together

• Join a fast-growing company where ambitious careers thrive

Selection Process Stages

1. Interview with Talent Acquisition

2. Technical Challenge

3. Interview with Technical Management

4. Evidence Storage

As part of our commitment to Information Security and in compliance with the requirements of the ISO 27001 standard (item 7.2, clause d), we would like to inform you that in future stages of the selection process, you will be required to provide proof of the skills and qualifications mentioned in your resume (such as diplomas and certificates). This verification is mandatory and essential to ensure compliance with our governance standards prior to hiring.

---

Some of the benefits offered by Indicium:

Professional Development

• Structured career path

• 100% subsidized certifications

• Weekly English classes

• Technical mentorship program (sponsorship)

• Participation in real Generative AI projects

• Opportunity to serve as an instructor at Indicium Academy (extra compensation)

Environment and Culture

• Data-driven culture

• Autonomy and a high level of trust

• Collaborative and technical environment

• Modern management and feedback structure

• Accelerated company growth

Other Benefits

• Employee referral program with bonuses

• Budget for training and events

• Flexible hours

• Partial remote work