Symphony Solutions
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What is the project, and why should you care?
Symphony Solutions is a Cloud- and AI-driven IT company headquartered in the Netherlands. We deliver tailored software solutions across Healthcare, Wellbeing, Airline, and other industries. Since 2008, we’ve been providing full-cycle software development, data and analytics, cloud engineering, ML & data engineering service, full-cycle development of AI solutions, and digital marketing orchestration for clients across Western Europe and North America.
Our solution is one of Symphony’s most innovative projects — an AI-powered personal intelligence platform that acts as a digital twin and “second brain.” It combines Voice services, multi-agents, external memory architecture, and LLM fine‑tuning to simplify complex digital interactions and provide personalized insights for users.
As the AI Solution Architect, you’ll play a pivotal role in designing the platform’s technical and AI foundations, ensuring its security, scalability, reliability, and intelligence.
Core Experience
7+ years of experience in software development (Python, Kotlin, Java, or C#), including 2+ years in solution or AI architecture.
Proven track record in AI/ML system design, integrating speech recognition (Speech to Text, Text to Speech, Speech to Speech), NLP, and contextual search, development of Gen-AI-based solutions, including RAG, LLM fine‑tuning, and real‑time speech handling.
Experience leading cross‑functional teams (AI, data, mobile, and backend engineers).
Deep understanding of mobile and cloud integration patterns.
Familiarity with Agile/Lean delivery and startup‑like MVP development environments.
Architecture & Cloud Proficiency
Expertise in GCP (Vertex AI, Cloud Run, Firestore, BigQuery ML, Serverless, Firebase and Postgres); AWS and Azure also acceptable.
Strong grasp of microservice, event‑driven, and serverless architectures.
CI/CD, containerization, and observability experience (GitHub Actions, Kubernetes, Docker, Prometheus, Grafana), experience working with vector and graph databases.
Experience implementing privacy‑first AI architectures (GDPR‑compliant data storage, anonymization, zero‑knowledge).
AI & GenAI Expertise
Practical understanding of LLMs, LLM fine‑tuning, RAG, multi‑modality, Agentic AI, and Multi‑agent architecture.
Hands‑on experience with LangChain, LlamaIndex, or AutoGen for model orchestration.
Knowledge of vector databases (Pinecone, Qdrant, Weaviate) and contextual memory design.
Familiarity with speech‑to‑text and TTS models (Whisper, Azure Cognitive Services, ElevenLabs).
Understanding of prompt engineering, meta prompting, and evaluation frameworks (TruLens, Vertex Evals).
Awareness of AI trust, explainability, and bias mitigation practices.
Experience with data ingestion and transformation pipelines (Airflow, Kafka, Spark).
Familiarity with embedding‑based search systems and knowledge graph structures.
Understanding of semantic memory models for personal assistant applications.
Soft Skills
Excellent stakeholder communication and technical storytelling.
Consulting mindset — ability to shape technical vision based on evolving business goals.
Capable of leading AI discovery workshops, technical PoCs, and pre‑sales solution design.
Collaborative leadership, inspiring innovation and ownership across the team.
Preferred Qualifications
Master’s degree in Computer Science, AI, or Data Engineering.
Nice to have certifications: AWS ML Specialty, Google ML Engineer, or Cloud Architect (any platform).
Strong understanding of AI governance, trust, and responsible AI principles.
Proven delivery record in AI companion or context‑aware assistant projects.
Mission
Define and drive the AI architecture and technical direction for the platform.
Transform business goals (e.g., digital twin, second brain, contextual AI) into scalable and production‑ready solutions.
Collaborate with Product Owner, Delivery Manager, and AI engineers to align strategy, feasibility, and innovation.
Key Responsibilities
Architect end‑to‑end architecture and design of the application, including its components: mobile apps, real‑time voice handling, AI agents, and cloud infra services.
Design agentic orchestration pipelines that allow autonomous collaboration between AI agents.
Oversee the integration of LLMs, embeddings, vectors, networks, and other databases into the core memory framework.
Define data privacy and ethical AI guidelines for the product.
Support PoC and MVP phases, validating approaches for multimodal (voice/text) interactions.
Mentor engineering teams in AI‑first architecture and MLOps/LLMOps best practices.
Lead technical feasibility assessments and manage trade‑offs between innovation and scalability.
Collaborate on AI roadmap evolution toward a fully personalized, on‑device digital twin.
Expected Results
Deliver a robust AI architecture blueprint.
Co‑lead the Agentic Orchestration Layer design and deployment for internal and production use.
Implement end‑to‑end LLM evaluation & monitoring within 6 months of MVP launch.
Enable continuous learning and improvement loops across AI components (speech, memory, reasoning).
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Information Technology
Industries IT Services and IT Consulting
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What is the project, and why should you care?
Symphony Solutions is a Cloud- and AI-driven IT company headquartered in the Netherlands. We deliver tailored software solutions across Healthcare, Wellbeing, Airline, and other industries. Since 2008, we’ve been providing full-cycle software development, data and analytics, cloud engineering, ML & data engineering service, full-cycle development of AI solutions, and digital marketing orchestration for clients across Western Europe and North America.
Our solution is one of Symphony’s most innovative projects — an AI-powered personal intelligence platform that acts as a digital twin and “second brain.” It combines Voice services, multi-agents, external memory architecture, and LLM fine‑tuning to simplify complex digital interactions and provide personalized insights for users.
As the AI Solution Architect, you’ll play a pivotal role in designing the platform’s technical and AI foundations, ensuring its security, scalability, reliability, and intelligence.
Core Experience
7+ years of experience in software development (Python, Kotlin, Java, or C#), including 2+ years in solution or AI architecture.
Proven track record in AI/ML system design, integrating speech recognition (Speech to Text, Text to Speech, Speech to Speech), NLP, and contextual search, development of Gen-AI-based solutions, including RAG, LLM fine‑tuning, and real‑time speech handling.
Experience leading cross‑functional teams (AI, data, mobile, and backend engineers).
Deep understanding of mobile and cloud integration patterns.
Familiarity with Agile/Lean delivery and startup‑like MVP development environments.
Architecture & Cloud Proficiency
Expertise in GCP (Vertex AI, Cloud Run, Firestore, BigQuery ML, Serverless, Firebase and Postgres); AWS and Azure also acceptable.
Strong grasp of microservice, event‑driven, and serverless architectures.
CI/CD, containerization, and observability experience (GitHub Actions, Kubernetes, Docker, Prometheus, Grafana), experience working with vector and graph databases.
Experience implementing privacy‑first AI architectures (GDPR‑compliant data storage, anonymization, zero‑knowledge).
AI & GenAI Expertise
Practical understanding of LLMs, LLM fine‑tuning, RAG, multi‑modality, Agentic AI, and Multi‑agent architecture.
Hands‑on experience with LangChain, LlamaIndex, or AutoGen for model orchestration.
Knowledge of vector databases (Pinecone, Qdrant, Weaviate) and contextual memory design.
Familiarity with speech‑to‑text and TTS models (Whisper, Azure Cognitive Services, ElevenLabs).
Understanding of prompt engineering, meta prompting, and evaluation frameworks (TruLens, Vertex Evals).
Awareness of AI trust, explainability, and bias mitigation practices.
Experience with data ingestion and transformation pipelines (Airflow, Kafka, Spark).
Familiarity with embedding‑based search systems and knowledge graph structures.
Understanding of semantic memory models for personal assistant applications.
Soft Skills
Excellent stakeholder communication and technical storytelling.
Consulting mindset — ability to shape technical vision based on evolving business goals.
Capable of leading AI discovery workshops, technical PoCs, and pre‑sales solution design.
Collaborative leadership, inspiring innovation and ownership across the team.
Preferred Qualifications
Master’s degree in Computer Science, AI, or Data Engineering.
Nice to have certifications: AWS ML Specialty, Google ML Engineer, or Cloud Architect (any platform).
Strong understanding of AI governance, trust, and responsible AI principles.
Proven delivery record in AI companion or context‑aware assistant projects.
Mission
Define and drive the AI architecture and technical direction for the platform.
Transform business goals (e.g., digital twin, second brain, contextual AI) into scalable and production‑ready solutions.
Collaborate with Product Owner, Delivery Manager, and AI engineers to align strategy, feasibility, and innovation.
Key Responsibilities
Architect end‑to‑end architecture and design of the application, including its components: mobile apps, real‑time voice handling, AI agents, and cloud infra services.
Design agentic orchestration pipelines that allow autonomous collaboration between AI agents.
Oversee the integration of LLMs, embeddings, vectors, networks, and other databases into the core memory framework.
Define data privacy and ethical AI guidelines for the product.
Support PoC and MVP phases, validating approaches for multimodal (voice/text) interactions.
Mentor engineering teams in AI‑first architecture and MLOps/LLMOps best practices.
Lead technical feasibility assessments and manage trade‑offs between innovation and scalability.
Collaborate on AI roadmap evolution toward a fully personalized, on‑device digital twin.
Expected Results
Deliver a robust AI architecture blueprint.
Co‑lead the Agentic Orchestration Layer design and deployment for internal and production use.
Implement end‑to‑end LLM evaluation & monitoring within 6 months of MVP launch.
Enable continuous learning and improvement loops across AI components (speech, memory, reasoning).
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Information Technology
Industries IT Services and IT Consulting
Referrals increase your chances of interviewing at Symphony Solutions by 2x
Get notified about new Solutions Architect jobs in
Poland .
We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.
#J-18808-Ljbffr