LLM Full Stack Engineer Associate Manager at Accenture

Heredia, Heredia Province, Costa Rica

Apply Now

Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Professional Services, AIIndustries

Requirements

Expertise in designing and evolving enterprise AI architecture blueprints, with emphasis on Generative AI, Large Language Models (LLMs), and multimodal models (text, vision, audio)
Strong knowledge of technology evaluation, selection, reference architectures, implementation roadmaps, and platform enablement across data, models, operations, security, governance, observability, and cost/performance optimization
Ability to lead multidisciplinary workstreams, align stakeholders, and guide solutions from Proof of Concept (POC) to production with Responsible AI practices
Proficiency in building and operationalizing AI foundation components, including data ingestion/curations, vector search, RAG pipelines, model serving gateways, feature/context stores, prompt management/versioning, evaluation tools, and LLMOps
Skills in designing custom architectural components like model routing, safety/guardrail services, retrieval/reranking services, caching layers, and policy enforcement
Experience in AI optimization for speed, reliability, cost-effectiveness, performance, and availability
Knowledge of end-to-end AI governance, including security, Responsible AI controls, data privacy, PII protection, policy enforcement, identity/access control, content safety, model risk assessment, auditability, and monitoring
Capability to establish observability for AI systems, covering metrics, logs, tracing, telemetry, cost monitoring (tokens/infrastructure), quality/safety metrics, drift detection, and incident response

Responsibilities

Engage with clients and stakeholder teams owning source systems and data platforms to define integration strategies, align interfaces and data flows, and ensure seamless incorporation of enterprise assets into scalable AI foundation components and solutions
Define and evolve the enterprise AI architecture blueprint, including LLM and multimodal capabilities, ensuring alignment with business strategy and IT standards
Assess, compare, and recommend technology options across data platforms, model development/serving, orchestration, observability, security, and governance; capture choices, rationale, benefits, and drawbacks
Develop implementation roadmaps to transition from current state to scalable AI foundation, sequencing capabilities, platforms, and integrations for progressive rollout
Build and operationalize end-to-end AI foundation components: data ingestion/curations, vector search/RAG pipelines, model serving gateways, feature/context stores, prompt management/versioning, evaluation tools, and LLMOps
Design and build custom architectural components where needed, such as model routing, safety/guardrail services, retrieval/reranking services, caching layers, and policy enforcement for scale and reusability
Optimize AI environment for fast, reliable, cost-effective model training and operation, meeting performance and availability targets
Implement end-to-end AI governance with security and Responsible AI controls: data privacy/PII protection, policy enforcement, identity/access control, content safety, model risk assessment, auditability, and continuous monitoring
Establish observability for AI systems: metrics, logs, tracing, telemetry, cost monitoring (tokens/infrastructure), quality/safety metrics, drift detection, and incident response

Skills

LLM

Generative AI

AI Architecture

Multimodal Models

Reference Architectures

Implementation Roadmaps

Platform Enablement

Data

MLOps

Security

Governance

Observability

Responsible AI

Proof of Concept

Production Deployment

Accenture

Global professional services for digital transformation

About Accenture

Accenture provides a wide range of professional services, including strategy and consulting, technology, and operations, to help organizations improve their performance. Their services assist clients in navigating digital transformation, enhancing operational efficiency, and achieving sustainable growth. Accenture's offerings include cloud migration, cybersecurity, artificial intelligence, and data analytics, which are tailored to meet the needs of various industries such as financial services, healthcare, and retail. What sets Accenture apart from its competitors is its extensive industry knowledge and ability to deliver comprehensive solutions that address both immediate challenges and long-term goals. The company's aim is to support clients in reducing their environmental impact while driving innovation and growth.

Dublin, IrelandHeadquarters

1989Year Founded

$8.5MTotal Funding

IPOCompany Stage

Consulting, Enterprise Software, CybersecurityIndustries

10,001+Employees

Risks

Rapid AI advancements may outpace Accenture's current capabilities, risking competitive disadvantages.

Integration challenges from multiple acquisitions could affect Accenture's operational efficiency.

The rise of AI-driven startups may disrupt Accenture's market share in customer service solutions.

Differentiation

Accenture's acquisitions enhance its capabilities in digital twin technology for financial services.

The company is expanding its expertise in net-zero infrastructure through strategic acquisitions.

Accenture's focus on software-defined vehicles positions it as a leader in automotive innovation.

Upsides

Accenture's investment in EMTECH supports central bank modernization amid digital currency evolution.

The acquisition of Award Solutions boosts Accenture's presence in the growing 5G and IoT markets.

Accenture's strategic acquisitions align with high-growth markets like digital twins and net-zero projects.

Land your dream remote job 3x faster with AI

Try Jobo Free