Senior Forward Deployed Engineer FSI

Indicium AI

Brasil

Presencial

BRL 250 000 - 450 000

Tempo integral

14 dias+

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Vantagens oferecidas por esta oferta de emprego

Weekly English classes

Technical mentorship program (sponsor)

Partial remote work

Flexible hours

Budget for training and events

Resumo da oferta

Indicium AI is seeking a Senior Forward Deployed Engineer to lead complex client-facing data and AI projects. You will drive diagnostics, architecture, implementation and knowledge transfer, collaborating with Data, Analytics and AI Engineers across global client environments.

Ideal candidates will have advanced SQL/Python, modern data stack expertise, cloud experience and strong executive communication skills, with a track record in delivering production-grade AI solutions at scale.

Qualificações

Experience leading end-to-end data and AI projects across data engineering, analytics engineering, data science or AI engineering.
Proven client-facing experience in consultative or technical implementation roles.
Advanced mastery of SQL, Python and Modern Data Stack tools (dbt, Airflow, Spark).
Experience with LLMs, RAG, agent development and fine‑tuning, including model evaluation and observability.
Proficiency with cloud services (AWS, GCP or Azure) and data infrastructure.

Responsabilidades

Lead complex end-to-end data and AI projects for clients, covering diagnostics, architecture, implementation, delivery and knowledge transfer.
Define technical and architectural approaches for data and AI solutions, balancing business, technology and operational constraints.
Act as a senior technical consultant alongside client leadership, influencing decisions and managing stakeholder conflicts.
Coordinate internal cross-functional teams (Data Engineers, Analytics Engineers, AI Engineers) to ensure alignment and on-time delivery.
Lead architecture and implementation of generative and agentic AI solutions (LLMs, RAG, multi-agent systems, fine-tuning, evaluation).
Develop and deploy MCP servers and integrations extending agent capabilities within the client’s enterprise infrastructure.
Evaluate and integrate AI providers and tools (OpenAI, Anthropic Claude, Google Gemini, Bedrock) considering cost, latency, security and regulatory compliance.
Identify and present project expansion opportunities to client and commercial team.
Ensure governance, security and compliance of data and AI solutions in client environments.
Establish MLOps practices: versioning, drift monitoring, pipelines, experiment tracking, secure deployment.
Mentor Junior and Mid-level FDEs and lead technical management of projects with defined scope, milestones and success metrics.
Build reusable accelerators, frameworks and contribute to Indicium’s internal solutions and roadmap.

Conhecimentos

Data Engineering

Analytics Engineering

AI Engineering

Data Science

Executive Communication

Cloud Platforms

Client Facing

Technical Leadership

Autonomy

Strategic Vision

Ferramentas

dbt

Airflow

Spark

BI platforms

AWS

GCP

Azure

Descrição da oferta de emprego

Company Overview

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. With over 600 AI experts, 50+ enterprise clients and five global locations, we collaborate with partners such as Anthropic, Databricks, AWS, OpenAI and Microsoft to deliver modern AI with speed, clarity and lasting impact.

About The Opportunity

The Senior Forward Deployed Engineer (FDE) is the primary technical and advisory reference at the client. The role combines technical depth in AI Engineering—LLMs, RAG, agents and MLOps—with a consultative vision and the ability to operate directly within the client’s environment. You will lead highly complex data and AI projects from end to end, influencing strategic decisions and serving as a technical ambassador for Indicium.

As a global company, we offer career opportunities across Europe and the Americas. Please indicate in your application if you are available to work abroad and if you hold a European passport.

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—, influence strategic decisions and manage stakeholder conflicts
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 communicate results 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, guiding 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) and its regulatory dynamics, risk structures, compliance requirements and operational standards
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