3 days ago

AI Architect – Agentic Systems (LLM & Multi-Agent Solutions)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Job Summary

Design and lead the implementation of production-grade multi-agent (agentic) AI systems in enterprise environments. You’ll architect multi-agent workflows, define how LLM-powered agents interact with enterprise data platforms, APIs/tools, and operational processes, and guide systems from PoC to production with cost, security, privacy, and responsible AI guardrails. Partner with data, platform, and engineering teams to establish observability, memory strategies, and reliability improvements for scalable, dependable agent behavior.

Location: Buenos Aires

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Design multi-agent architectures (task decomposition, orchestration, coordination patterns) and define agent interactions with enterprise systems.
•Lead agentic systems from PoC to production, including model, cost, security, privacy, and responsible AI guardrails.
•Establish observability (tracing, feedback loops, and controls) to manage agent behavior and reliability.
•Define memory strategies (short-term, long-term, contextual grounding) for agent context management.
•Collaborate with data, platform, and engineering teams to integrate AI into core systems and guide teams on best practices for scalable, reliable AI systems.

Pay and Benefits

Equity and Bonus:Equity

Perks:EquityAnnual BonusLearning Budget

Key Requirements

•Strong background in software architecture and distributed systems.
•Hands-on experience building complex LLM-based applications and designing orchestration/workflow systems.
•Solid understanding of RAG architectures, retrieval optimization, and retrieval quality.
•Strong grasp of LLM fundamentals (including Transformer architecture and training/fine-tuning concepts) and how model behavior/limitations impact outcomes.
•Experience with multi-agent frameworks and platforms for managing the lifecycle of generative AI applications and agents.

Languages:English

Tech Stack:PythonLangChainSemantic KernelAgent FrameworkCrewAIAmazon BedrockAWSGoogle Vertex AIGCPAzure AI FoundryMCPUCPA2AAP2

Company Brief

Endava Technology

Provides IT services and digital engineering, delivering software development, automation, and consulting to enterprises across financial services, payments, telecommunications, and retail to accelerate digital transformation.

Industry: Consulting

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: London, United Kingdom

Founded: 2000

Website LinkedIn

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Endava Technology

3 days ago

AI Architect – Agentic Systems (LLM & Multi-Agent Solutions)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Job Summary

Location: Buenos Aires

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Design multi-agent architectures (task decomposition, orchestration, coordination patterns) and define agent interactions with enterprise systems.
•Lead agentic systems from PoC to production, including model, cost, security, privacy, and responsible AI guardrails.
•Establish observability (tracing, feedback loops, and controls) to manage agent behavior and reliability.
•Define memory strategies (short-term, long-term, contextual grounding) for agent context management.
•Collaborate with data, platform, and engineering teams to integrate AI into core systems and guide teams on best practices for scalable, reliable AI systems.

Pay and Benefits

Equity and Bonus:Equity

Perks:EquityAnnual BonusLearning Budget

Key Requirements

•Strong background in software architecture and distributed systems.
•Hands-on experience building complex LLM-based applications and designing orchestration/workflow systems.
•Solid understanding of RAG architectures, retrieval optimization, and retrieval quality.
•Strong grasp of LLM fundamentals (including Transformer architecture and training/fine-tuning concepts) and how model behavior/limitations impact outcomes.
•Experience with multi-agent frameworks and platforms for managing the lifecycle of generative AI applications and agents.

Languages:English

Tech Stack:PythonLangChainSemantic KernelAgent FrameworkCrewAIAmazon BedrockAWSGoogle Vertex AIGCPAzure AI FoundryMCPUCPA2AAP2

Company Brief

Endava Technology

Industry: Consulting

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: London, United Kingdom

Founded: 2000

Website LinkedIn